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https://www.databricks.com/dataaisummit/speaker/risha-ravindranath

Risha Ravindranath - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRisha RavindranathSr Manager, Data Governance at Comcast AdvertisingBack to speakersRisha Ravindranath brings 10+ years of experience in Data Governance and Business Analysis. She is a highly involved business analyst who expertly brings solutions together to drive end-to-end data governance programs integrated with technical solutions. Risha currently is a Senior Manager of Data Governance at Comcast Effectv.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/resources/webinar/goodbye-data-warehouse-hello-lakehouse?itm_data=unitycatalog-promocard-goodbyedwbigrock

The Case for Moving to the Lakehouse | DatabricksWebinarThe Case for Moving to the Lakehouse Learn how Chick-fil-A, Inc. and Zurich Insurance speed up innovation with the lakehouseMay 18, 2023 | 8 AM PT / 4 PM BSTRunning data warehouses for business analytics and data lakes for AI is costly, complex, inefficient — and unnecessary. In fact, as Large Language Model applications like ChatGPT disrupt everything, thousands of organizations are making generative AI their single biggest technological shift (and boardroom priority). The need to sync data between different systems to bring organizational-wide, high-quality data together has never been greater. Join us to learn about the lakehouse and why it's the right data architecture for all your data, analytics and AI use cases. Then we’ll cover integrating with modern tools you have today such as Fivetran and dbt, or new technologies you may adopt tomorrow, to access the freshest data from anywhere.Learn from Databricks, Fivetran and dbt Labs experts how to:Automate data movement and transform raw data into analytics-ready tables using your favorite tools like Fivetran and dbtUnify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BIReduce costs and get started in seconds with on-demand, elastic SQL serverless computeUse automated and real-time lineage to monitor end-to-end data flowGo from ingest to insight with Databricks SQL and Unity Catalog for best-in-class data warehousing, fine-grained governance, and sharing on the LakehouseExpand sharing and collaboration beyond just data with Delta Sharing and Databricks MarketplaceThis interactive session will come to life with demos, customer stories and Q&A. Plus, you’ll get a $100 credit toward a wide selection of Databricks certifications. All you have to do is register, and we’ll show you how to claim this special offer in the confirmation email.SpeakersReynold XinCo-founder & Chief ArchitectDatabricksDrew BaninCo-Founder & Chief Product OfficerDbt LabsBill InmonFounderForest Rim TechnologyAaron ReesePrincipal Enterprise Architect, Advanced AnalyticsChick-fil-A, Inc.José Luis Sánchez Ros Head of Data Solution ArchitectureZurich Insurance Company LtdMark Van de WielField CTOFivetranErika EhrliSenior Director of Product MarketingDatabricksShant HovsepianPrincipal Software EngineerDatabricksPearl UbaruSr. Technical Marketing EngineerDatabricksJoin UsEvent Co-sponsor: Databricks (Databricks Privacy Policy) Event Co-sponsor: Fivetran (Fivetran Privacy Policy) Event Co-Sponsor: dbt Labs (dbt Labs policy)ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/tomer-patel

Tomer Patel - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTomer PatelSoftware Engineering Manager at Akamai TechnologiesBack to speakersTomer Patel is an Engineering Manager at Akamai. He manages, builds, implements, and maintains scaled cyber security analytics applications on top of Azure and Databricks. He currently manages 4 teams that focus on Data Engineering, Interactive Analytics product, and Devops. Tomer has a Bachelor's degree in Computer Science from The Hebrew University of Jerusalem and a Master of Business Administration (MBA) from Bar-Ilan University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/de/solutions/industries/federal-government

Data Analytics und KI für Bundesbehörden | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse. Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt. Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT   Entdecken Sie das Lakehouse für die Fertigung Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023 Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWData Analytics und KI für BundesbehördenNutzen Sie Innovationen, um mit Daten und Machine Learning bessere öffentliche Dienste anzubieten.Durch die Federal Data Strategy und AI Executive Order ist klar, dass sich die US-Regierung auf die Modernisierung ihrer Data-Analytics- und Warehousing-Funktionen konzentriert.Die Databricks Lakehouse Platform ermöglicht es Bundesbehörden, das volle Potenzial ihrer Daten auszuschöpfen, um ihre Ziele zu erreichen und Bürgern einen besseren Service zu bieten.Befähigung von Bundesbehörden, Daten und KI zu nutzen, um Missionsziele zu erreichenVon führenden Behörden des öffentlichen Sektors als vertrauenswürdig eingestuft+ jeder sonstige Apache Spark™-kompatible ClientSehen Sie sich an, wie Branchenführer Databricks nutzen, um das Erlebnis für Bürger in allen öffentlichen Diensten zu verbessern.Neueste Blogbeiträge, Webinare und FallstudienWarum Databricks für die BundesbehördenModernisieren Ihrer Data Analytics130 Zeichen Modernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis für Patienten und Ärzte mit der schnellsten DNAQSeq-Pipeline in großem Umfang.Effektive und effiziente Erbringung von Missionsergebnissen130 Zeichen Modernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis für Patienten und Ärzte mit der schnellsten DNAQSeq-Pipeline in großem Umfang.Schaffung besserer Erlebnisse für die Bürger130 Zeichen Modernisieren Sie Ihre Technologie und verbessern Sie das Erlebnis für Patienten und Ärzte mit der schnellsten DNAQSeq-Pipeline in großem Umfang.Mehr InformationenUmfassende Compliance für eine schnelle und einfache Betriebserlaubnis (ATO)Databricks hat ATOs für die Regionen, Netzwerke und Konformitätskontrollen erreicht, die Ihre Missionsziele unterstützenCloudsC2S SC2S GovCloud Public Cloud NetzwerkeÖffentlich NIPR SIPR JWICS Compliance-KontrollenFedRAMP FedRAMP-High FISMA IL5 IL6 ICS-503 Wie Databricks Innovationen für die Bundesbehörden fördertGesundheitswesenVerbessern Sie die Lieferung und Qualität von Gesundheitsdiensten für die Bürger mit leistungsstarken Analysen und einer 360°-Ansicht der Patienten. Patient 360  Optimierung der Lieferkette  Versicherungsmanagement  Genomik  Erforschung und Bereitstellung von MedikamentenVerteidigungNutzen Sie die Möglichkeiten der prädiktiven Analytics für Geo-, IoT- und Überwachungsdaten, um den Betrieb zu verbessern und das Land zu schützen.  Logistik Vorausschauende Wartung  Überwachung und Aufklärung  Strafverfolgung und BereitschaftHomeland SecurityErkennen und verhindern Sie kriminelle Aktivitäten und nationale Bedrohungen mit Echtzeit-Analysen und datengesteuerten Entscheidungen.  Zoll und Grenzschutz  Einwanderung und Staatsbürgerschaft  Terrorismusbekämpfung  Verwaltung der Nothilfe von BundesbehördenÖffentliche Behörden/HandelErkennen Sie Anomalien mit Machine Learning proaktiv, um Risiken zu mindern und betrügerische Aktivitäten zu verhindern. Steuerbetrug und -einzug  Prozess- und Betriebsmanagement  Verwaltung von Finanzhilfen  Kunde 360EnergieVerbessern Sie das Energiemanagement mit Dateneinblicken, die die Energieresilienz und Nachhaltigkeit sicherstellen.  Sicherheit der Energieinfrastruktur  Intelligenteres Energiemanagement  Energieexploration  Zuverlässigkeit des StromnetzesGeheimdiensteNutzen Sie Echtzeiteinblicke, um fundierte Entscheidungen zu treffen, die sich auf die Sicherheit unserer Bürger und der Welt auswirken können.  Bedrohungserkennung  Neutralisierung von Cyberangriffen  Geheimdienstliche Überwachung und Aufklärung  Social Media AnalyticsRessourcenKundenberichteFörderung der digitalen Transformation, damit Patienten bei CMS immer an oberster Stelle stehenBewährte Methoden der Data Governance – Lehren aus den Centers von Medicare und Medicaid ServicesLehren aus der Modernisierung der USCIS Data Analytics PlatformModernisierung der Air Force mit Big Data und KIWebinareSchnelle Reaktion im Krankenhausbetrieb mithilfe von Daten und KI während der COVID-19-PandemieGeodatenanalyse und KI im öffentlichen SektorEine moderne Architektur zur Datenanalyse für RegierungenBessere Erkennung von Bedrohungen mit Big Data und KINeuigkeitenAzure Databricks erreicht FedRAMP High Authorization in Microsoft Azure Government (MAG)Sicherheit auf Regierungsniveau in der AWS CloudUnified Analytics für Regierungen und BehördenStärkung der U.S. Intelligence Community durch missionskritische Analytics und KIGipfelgesprächeAutomatisierung des systemweiten Informationsmanagements (SWIM) der Federal Aviation Administration (FAA) bei der Datenerfassung und -analyseGeospatial Analytics in großem Maßstab: Analyse von Bewegungsmustern während einer PandemieMöchten Sie loslegen?Wir würden uns freuen, Ihre Geschäftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann. Kostenlos testenKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter „Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte

https://www.databricks.com/try-databricks

Try Databricks | DatabricksTry Databricks free Test-drive the full Databricks platform free for 14 days on your choice of AWS, Microsoft Azure or Google Cloud.Simplify data ingestion and automate ETLIngest data from hundreds of sources. Use a simple declarative approach to build data pipelines.Collaborate in your preferred languageCode in Python, R, Scala and SQL with coauthoring, automatic versioning, Git integrations and RBAC.12x better price/performance than cloud data warehousesSee why over 7,000 customers worldwide rely on Databricks for all their workloads from BI to AI.Create your Databricks account1/2First nameLast NameEmailCompanyTitlePhone (Optional)SelectCountryContinuePrivacy Notice (Updated)Terms of UseYour Privacy ChoicesYour California Privacy Rights

https://www.databricks.com/kr/events

Databricks 이벤트 | DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 | 오전 8시(태평양 표준시)   제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOWDatabricks 이벤트예정된 Databricks 모임, 웨비나, 컨퍼런스 등을 살펴보세요.Data + AI Summit 20236월 26일 ~ 29일경험 방식 선택 - 현장에 직접 참석하거나 기조 연설 라이브스트리밍에 온라인으로 참석하고 참여할 세션을 선택하세요.지금 등록하기Loading...Browse All Upcoming Events제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark 및 Spark 로고는 Apache Software Foundation의 상표입니다.개인 정보 보호 고지|이용약관|귀하의 개인 정보 선택|귀하의 캘리포니아 프라이버시 권리

https://www.databricks.com/dataaisummit/speaker/bradley-axen/#

Bradley Axen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBradley AxenMachine Learning Engineer at BlockBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/john-thompson/#

John Thompson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJohn ThompsonGlobal Head, Artificial Intelligence at EYBack to speakersJohn is an international technology executive with over 35 years of experience in the fields of data, advanced analytics, and artificial intelligence (AI). He is currently the Global Head of AI at EY. John has built start-up organizations from the ground up and he has reengineered business units of Fortune 500 firms to reach their potential. He has directly managed and run - sales, marketing, consulting, support, and product development organizations.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/#

Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI. Register NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you’re an engineering wizard, ML pro, SQL expert — or you want to learn how to build, train and deploy LLMs — you’ll be in good company. See all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI — and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer. SessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more. Explore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark™, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto/Trino, DuckDB and much more. You’ll also get a first look at new products and features in the Databricks Lakehouse Platform. Browse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party. Learn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at “birds of a feather” meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark™, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world See agendaDon’t miss this year’s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/fr/product/databricks-sql

Databricks SQL | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT   Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWPromotion Databricks SQL – économisez plus de 40 %Profitez de notre promotion de 15 mois sur SQL Serverless et le tout nouveau SQL ProEn savoir plusDatabricks SQLLe meilleur data warehouse est un lakehouseDémarrerRegarder la démo WEBINAR • Goodbye, Data Warehouse. Hello, Lakehouse. Attend on May 18 and get a $100 credit toward a Databricks certification course Register nowDatabricks SQL (DB SQL) est un data warehouse serverless basé sur la plateforme Databricks Lakehouse. Capable d'exécuter toutes vos applications SQL et BI à grande échelle, il combine un rapport performance / prix jusqu'à 12 fois supérieur, un modèle de gouvernance unifié, des API et des formats ouverts ainsi que les outils de votre choix, sans vous lier à aucun fournisseur.Meilleur rapport performance / prixRéduisez les coûts et obtenez le meilleur rapport performance / prix, tout en vous libérant de la gestion, de la configuration et de l'évolution de votre infrastructure cloud avec le serverless.Gouvernance intégréeCréez un exemplaire unique de toutes vos données à l'aide de normes ouvertes et appliquez une couche de gouvernance unifiée à toutes les équipes de données à l'aide du SQL standard.Un écosystème richeUtilisez SQL et des outils comme Fivetran, dbt, Power BI ou Tableau conjointement avec Databricks pour ingérer, transformer et interroger toutes vos données in situ.Éliminez les silosDonnez à tous vos analystes les moyens d'accéder plus rapidement aux données les plus récentes à des fins d'analytique en aval en temps réel, et passez sans effort de la BI au ML.Comment ça marche ?Intégrations transparentes avec l’écosystème Simplicité d'utilisation Performant dans le monde réel Gouvernance centralisée Un lac de données ouvert et fiable comme fondementIngérez, transformez et orchestrez facilement les données, quelle que soit leur sourceTravaillez avec vos données, où qu'elles se trouvent. Les fonctionnalités clés en main permettent aux analystes et aux ingénieurs analytiques d'ingérer facilement des données de tout type de source, du stockage cloud aux applications d'entreprise comme Salesforce, Google Analytics ou Marketo, à l'aide de Fivetran. Tout est disponible en un clic. Ensuite, il vous suffit de gérer les dépendances et de transformer les données in situ. Pour cela, vous pouvez utiliser les fonctionnalités ETL intégrées du Lakehouse ou vos outils préférés comme dbt sur Databricks SQL pour des performances optimales. « En combinant Databricks et Fivetran, nous avons mis sur pied un pipeline de données à la fois robuste et moderne en un temps record. Fivetran offrait tous les connecteurs et toutes les intégrations dont nous avions besoin. »— Justin Wille, Directeur Insights et Analytique, Kreg ToolEn savoir plusChoisissez vos outils d'analytique et de BITravaillez en toute transparence avec les outils de BI les plus populaires comme Tableau, Power BI et Looker. Désormais, les analystes peuvent utiliser leurs outils favoris pour découvrir de nouveaux insights métier en s'appuyant sur les données les plus complètes et les plus récentes. Pour maximiser la collaboration, Databricks SQL permet également à chaque analyste d'identifier et de partager rapidement de nouveaux insights grâce à l'éditeur SQL intégré, aux visualisations et aux tableaux de bord. « Nous avons maintenant la certitude d'avoir à portée de main les données les plus récentes et les plus complètes pour alimenter nos tableaux de bord et nos rapports Power BI. »— Jake Stone, Senior Manager, Business Analytics, ButcherBoxEn savoir plusÉliminez la gestion des ressources grâce au calcul serverlessAvec Databricks SQL serverless, vous n'avez plus besoin de gérer, configurer ou faire évoluer l'infrastructure cloud sur le Lakehouse. Votre équipe de données a ainsi davantage de temps à consacrer à son cœur de mission. Les warehouses SQL Databricks fournissent un calcul SQL instantané et élastique, découplé du stockage. Convenant idéalement aux cas d’usage à forte concurrence, ils s’adaptent automatiquement pour fournir une simultanéité illimitée sans interruption. « Databricks SQL Serverless nous offre toute la puissance de Databricks SQL et permet une exploitation bien plus efficace de notre infrastructure. »— R. Tyler Croy, Director of Platform Engineering, ScribdEn savoir plusIntégralement conçu pour des performances optimalesDatabricks SQL a été résolument optimisé pour vous offrir les meilleures performances pour tous les outils, types de requêtes et applications du monde réel. Cela inclut Photon — le moteur de requête nouvelle génération — qui, combiné aux warehouses SQL, offre un rapport performance / prix jusqu'à 12 fois supérieur à celui des autres data warehouses dans le cloud. « Grâce aux analyses que nous effectuons sur la plateforme lakehouse Databricks, le temps nécessaire pour produire des insights à partir du comportement des audiences est passé de plusieurs semaines à quelques minutes. »— Stéphane Caron, Directeur Business Intelligence, CBC / Radio-CanadaEn savoir plusCentralisez le stockage et l'administration de toutes vos données avec le SQL standardCréez un seul exemplaire de toutes vos données à l'aide du format ouvert de Delta Lake pour éviter le verrouillage des données. Vous pouvez alors effectuer des analyses in situ et des opérations ETL / ELT sur votre Lakehouse, sans déplacer ni copier des données dispersées dans différents systèmes. Gouvernance fine, data lineage et SQL standard : ces outils facilitent la découverte, la sécurisation et la gestion de toutes vos données sur l'ensemble des clouds avec le Unity Catalog de Databricks. « Databricks joue un rôle essentiel dans nos activités. Son architecture de lakehouse nous offre en effet un moyen unifié de stocker, consulter et partager des données exploitables. »— Jagan Mangalampalli, Directeur Big Data, PunchhEn savoir plusBâti sur une fondation de données commune, alimenté par la plateforme LakehouseLa plate-forme Databricks Lakehouse fournit la solution de data warehouse la plus complète de bout en bout pour tous vos besoins d’analytique moderne, et bien plus encore. Obtenez des performances de classe mondiale pour un coût bien inférieur à celui des data warehouses cloud. Réduisez le délai entre l'acquisition des données brutes et les renseignements exploitables à grande échelle, et unifiez données en lot et en streaming. De plus, le Lakehouse permet aux équipes de données de passer sans effort de la description à l'analyse prédictive pour découvrir de nouveaux insights. « Databricks met à la disposition de nos équipes de données et d'analytique une plateforme unique pour consulter les données et les partager au sein d'ABN AMRO. Elles peuvent ainsi délivrer des solutions ML qui facilitent l'automatisation et génèrent des insights à l'échelle de l'entreprise. »— Stefan Groot, Directeur Ingénierie analytique, ABN AMROEn savoir plusMigrer vers DatabricksVous en avez assez des silos de données, de la lenteur des performances et des coûts élevés associés aux anciens systèmes comme Hadoop et aux entrepôts de données d'entreprise ? Migrez vers Databricks Lakehouse : la plateforme moderne pour tous vos cas d'utilisation de données, d'analyses et d'IA.Migrer vers DatabricksIntégrationsDes intégrations fluides avec l'écosystème offrent une flexibilité maximale à vos équipes data. Intégrez les données critiques de l'entreprise avec Fivetran, transformez-les sur place avec dbt et découvrez de nouveaux insights avec Power BI, Tableau ou Looker, le tout sans déplacer vos données dans un data warehouse existant.Ingestion de données et ETLGouvernance des donnéesBI et tableaux de bord+ tout autre client compatible Apache Spark™« Aujourd'hui, plus que jamais, les organisations ont besoin d'une stratégie de données offrant rapidité et agilité pour être adaptables. Alors que les entreprises migrent rapidement leurs données vers le cloud, nous constatons un intérêt croissant pour l'analytique dans le datalake. Databricks SQL offre une toute nouvelle expérience permettant aux clients d'exploiter des insights provenant de volumes massifs de données, avec les performances, la fiabilité et l'évolutivité dont ils ont besoin. Nous sommes fiers de nous associer à Databricks pour concrétiser cette opportunité. »- Francois Ajenstat, chef de produit, TableauTémoignages de clientsEn savoir plusDelta LakeContact partenairesUnity CatalogDelta Live tablesContenu associé Toutes les ressources dont vous avez besoin. Réunies au même endroit. Explorez notre bibliothèque de ressources : vous y trouverez des ebooks et des vidéos sur les avantages du lakehouse. Explorer les ressourcesEbooksCréer le Data Lakehouse par Bill Inmon, père du data warehousePourquoi le lakehouse est votre prochain data warehouseDonnées, analyses et gouvernance de l'IALe Grand Livre du Data EngineeringLa migration d'un data warehouse vers un data lakehouse en quelques motsÉvénementsTravaux internes du Lakehouse sur le Data + AI World TourWebinaire sur les bonnes pratiques en matière d'optimisation des performances sur le Lakehouse – Dans la vie d'une requêteFormation gratuite Databricks SQL – À la demandeLe meilleur data warehouse est un lakehouseBlogsDatabricks établit un record officiel de performance pour l'entreposage des donnéesAnnonce de la disponibilité générale de Databricks SQLÉvolution du langage SQL chez Databricks : standard Ansi par défaut et migrations plus faciles à partir des Data WarehousesIl n'a jamais été aussi simple de déployer dbt sur DatabricksTechniques de modélisation de data warehouse et mise en œuvre sur la plateforme de lakehouse DatabricksComment créer une solution d'analyse marketing avec Fivetran et dbt sur le lakehouse DatabricksPrêt à vous lancer ?Essai gratuitRejoignez la communautéProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie

https://www.databricks.com/dataaisummit/speaker/lakhan-prajapati/#

Lakhan Prajapati - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLakhan PrajapatiDirector of Architecture and Engineering at ZS associatesBack to speakersTechnology Enthusiast, Loves solving complex tech problems for the enterprise. Expertise in the field of cloud, data warehousing, and enterprise architectureLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/p/ebook/the-delta-lake-series

The Definitive Guide to Delta Lake Series | DatabricksSeriesBring fast analytics to your data lakeImprove quality, security and performance in your data lake.In “The Delta Lake Series”, we will explore how Delta Lake brings quality, reliability, security and performance to your data lake to enable a lakehouse architecture. Download this eBook series to understand the unique capabilities of Delta Lake, explore common use cases like streaming and learn how Delta Lake delivers substantial performance improvements for our customers.The eBook series breaks out into the following chapters:Chapter 01 — Fundamentals and PerformanceChapter 02 — FeaturesChapter 03 — LakehouseChapter 04 — StreamingChapter 05 — Customer Use CasesGet the SeriesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/cdn-cgi/l/email-protection#9dedeff4ebfcfee4ddf9fce9fcffeff4fef6eeb3fef2f0

Email Protection | Cloudflare Please enable cookies. Email Protection You are unable to access this email address databricks.com The website from which you got to this page is protected by Cloudflare. Email addresses on that page have been hidden in order to keep them from being accessed by malicious bots. You must enable Javascript in your browser in order to decode the e-mail address. If you have a website and are interested in protecting it in a similar way, you can sign up for Cloudflare. How does Cloudflare protect email addresses on website from spammers? Can I sign up for Cloudflare? Cloudflare Ray ID: 7c5c3ca7bcb282c6 • Your IP: Click to reveal 2601:147:4700:3180:15eb:de93:22f5:f511 • Performance & security by Cloudflare

https://www.databricks.com/fr/company/awards-and-recognition

Prix et distinctions | DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT   Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWPrix et distinctionsDécouvrez toutes les raisons pour lesquelles Databricks est récompensé par les leaders du secteur.Leader du Magic Quadrant 2022pour les systèmes de gestion des bases de données cloudCustomer Choice Award 2022 pour les systèmes de gestion des bases de données cloudLeader du Magic Quadrant 2021 pour les systèmes de gestion des bases de données cloudLeader du Magic Quadrant 2021 pour la Data Science et le Machine learningLakehouse – Hype Cycle sur les solutions de gestion des données, 2022Les entreprises à suivre en 2023Entreprises les plus innovantes en data scienceCloud 100AI 50America’s Best Startup EmployersMeilleurs lieux de travail dans le secteur des technologiesMeilleurs lieux de travail de la région de la Baie de San FranciscoMeilleurs lieux de travail pour les MillennialsCNBC Disruptor 50Meilleurs lieux de travail en 2022Vous voulez en savoir plus ?Nous serions ravis de connaître vos objectifs commerciaux. Notre équipe de services fera tout son possible pour vous aider à réussir.ESSAYER GRATUITEMENT DATABRICKSProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie

https://www.databricks.com/dataaisummit/speaker/tathagata-das

Tathagata Das - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingTathagata Das DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/pouya-barrach-yousefi/#

Pouya Barrach-Yousefi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPouya Barrach-YousefiData Pro and Director Strategic Accounts at ProphecyBack to speakersIn the 6 years at IQVIA prior to joining Prophecy, Pouya was a Data Science Developer and tech lead for the Analytics Center of Excellence, then joined the global Data Science & Advanced Analytics team as an Associate Data Science Director to focus on delivering commercial AIML solutions for pharma clients, and finally as Director of Enterprise AIML Strategy he led data, data science, and machine learning improvements across IQVIA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/deepak-sekar/#

Deepak Sekar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDeepak SekarSr. Solution Architect at DatabricksBack to speakersA Data & AI enthusiast from the down under! Extensive experience in building Enterprise/ SMB Data & AI solutions in ASEAN and Australia/NZ across Energy & Utilities/ Oil & Gas/ Telecommunication/ Retail. I love guiding organizations to embrace data & unlock the never-ending value that data brings to them. Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/de/customers?itm_data=hp-promo-customerlogos-seeallcustomers

Kunden von
Databricks | DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse. Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt. Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT   Entdecken Sie das Lakehouse für die Fertigung Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023 Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWKunden von DatabricksEntdecken Sie, wie innovative Unternehmen aus allen Branchen die Databricks Lakehouse-Plattform für ihren Erfolg nutzenEmpfehlungen Kundenbericht Modernisierung von Finanzdienstleistungen mit Daten und KI Trotz der steigenden Akzeptanz von Big Data und KI sehen sich die meisten Finanzdienstleister immer noch mit erheblichen Herausforderungen bei Datentypen, Datenschutz und Umfang konfrontiert. Weiterlesen Kundenbericht Vorhersagen und Steigern des Customer Lifetime Value mit ML Kolibri Games befindet sich im Herzen Berlins und ist bekannt für seinen erfrischenden, von Spielern geführten Ansatz. Kolibri Games ist ein aufgehender Stern in der Szene der Spiele für Mobilgeräte. Die Hittitel Idle Miner Tycoon und Idle Factory Tycoon ziehen monatlich über 10 Millionen aktive Benutzer an. Weiterlesen Kundenbericht Shell führt innovative Energielösungen für eine sauberere Welt ein Databricks Lakehouse trägt dazu bei, Daten zu demokratisieren und Abläufe weltweit zu modernisieren Weiterlesen Kundenbericht Digitalisierung der Solaranlagen zur Förderung der betrieblichen Exzellenz Solytic, ein Unternehmen, das Solaranlagen überwacht und deren Daten analysiert, hat ein Ziel: die Nutzung von Solarenergie für jedermann zu vereinfachen. Weiterlesen Kundenbericht Verbinden Sie Millionen von Kunden mit dem größten 5G-Netzwerk Als einer der bekanntesten Mobilfunkanbieter in den USA hat sich T-Mobile zum Ziel gesetzt, das größte und schnellste 5G-Netz bereitzustellen. Weiterlesen Kundenbericht Aufbau einer energieeffizienten Welt Da die weltweite Nachfrage nach energieeffizienten Lösungen weiter steigt – von Klimasystemen über Solarmodule bis hin zu Windturbinen und Elektroautos – kann die Bedeutung von Daten für einen intelligenteren Betrieb nicht hoch genug eingeschätzt werden.  WeiterlesenAlle Kunden erkundenDer Daten-Team EffektDatenteams bilden eine vereinte Streitmacht, wenn es darum geht, die schwierigsten Probleme der Welt zu lösen.Erfahren Sie, wie →Ist Ihr Unternehmen die nächste Erfolgsgeschichte?KontaktRessourcenKundenberichtSo stellt Condé Nast seinen Kunden mithilfe von Databricks personalisierte Inhalte bereit.Mehr InformationenKundenberichtFinden Sie heraus, wie Apple und Disney+ mit Unified Analytics und KI riesige Erfolge feiernMehr InformationenKundenberichtErfahren Sie von Slawek Kierner, SVP, Chief Data & Analytics Officer bei Humana, mehr über die Rolle von Daten und KI im GesundheitswesenAnsehenMöchten Sie loslegen?Kostenlos testenKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter „Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte

https://www.databricks.com/fr/discover/beacons

Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing – all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark™, Delta Lake, MLflow and others. Don’t hesitate to reach out to them on social to see what they’re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.  UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark™ committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark™, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark™ adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark™.POLANDMaciej SzymkiewiczMaciej is an Apache Spark™ committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark™ committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark™, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select Databricks eventsSponsorship and swag for meetupsNominate a peerWe’d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone — including customers, partners, Databricks employees or even a current Beacon — is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/company/partners/consulting-and-si/partner-solutions/tredence-predictive-supply-risk-management

Predictive Supply Risk Management by Tredence and Databricks | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionPredictive Supply Risk Management by TredenceIndustry-specific solution developed by Tredence and powered by the Databricks Lakehouse PlatformContact usPower your supply risk decisionsCustomers today are faced with multiple supply risks including lack of in-transit visibility, disruptions caused by weather, and local events, among others. Tredence’s Predictive Supply Risk Management solution, built on the Databricks Lakehouse Platform, helps businesses meet supply risk challenges by providing a scalable, cloud-based solution that can be tailored to the specific needs of each organization. The platform’s flexibility and scalability allow businesses to keep pace with changing regulations and customer demands, and its comprehensive suite of tools helps identify and mitigate risks across the enterprise. Benefits of the Tredence Predictive Supply Risk Management solution are:Predicts order delays, identifies root causes and quantifies supply chain impactProvides real-time visibility with delay alerts using external and internal data Delivers prescriptive models and simulation to mitigate risksContact usResourcesWhitepaperLearn moreBlogLearn moreExplainer VideoLearn moreDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/aman-kapoor/#

Aman Kapoor - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAman KapoorHead of Data Platform at PetronasBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/suneel-konidala/#

Suneel Konidala - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSuneel KonidalaSr. Manager at AccentureBack to speakersSuneel is an accomplished leader in Data space for more than two decades. He is a lead partner champion at Accenture's Databricks practice. Suneel is well versed in multiple data and cloud technologies.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/beinan-wang

Beinan Wang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingBeinan WangSenior Staff Software Engineer at AlluxioBack to speakersDr. Beinan Wang is a Senior Staff Software Engineer from Alluxio and is the committer of PrestoDB. He is leading the engineer efforts of the next generation distributed cache. Prior to Alluxio, he was the Tech Lead of the Presto team in Twitter and he built large-scale distributed SQL systems for Twitter’s data platform. He has twelve-year experience of working on performance optimization. He received his Ph.D. in computer engineering from Syracuse University on distributed systems.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/company/careers/open-positions?location=washington%2C%20D.C.

Current job openings at Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOW OverviewCultureBenefitsDiversityStudents & new gradsCurrent job openings at DatabricksDepartmentLocationProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/vinit-doshi

Vinit Doshi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVinit DoshiSenior Manager at TredenceBack to speakersVinit Doshi leads the MLOps delivery practice at Tredence, He has over 14 years of experience in building and managing ML solutions with a focus on building scalable MLOPs practices for clients over the past 3 years.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/alexander-booth

Alexander Booth - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlexander BoothAssistant Director of Research & Development at Texas Rangers Baseball Club, LLCBack to speakersAlexander is a data scientist, data engineer, and application developer with extensive experience in using machine learning and artificial intelligence techniques, based on insights from big data, to communicate actionable decisions to management to help generate a competitive advantage. He specializes in Sports Analytics with a particular passion for learning how innovation and new technology can shape the game of baseball.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/product/pricing/serverless-realtime-inference

Model Serving Pricing | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWModel Serving PricingOverviewJobsDelta Live TablesDatabricks SQLData Science & MLModel ServingPlatform & Add-OnsCalculatorModel ServingMake live predictions in your apps and websites.Select planhelp me chooseStandardPremiumEnterpriseSelect cloudAWSAzureGoogle CloudSelect regionSelectLoading...Model Serving pricing examples Notes:1. The simple examples above are baseline configurations. Example 2 requires launch charge from cold start.2. Users may also select “scale to zero” or “very latency sensitive” options, which would change DBU emissions.FAQHow much memory is provided per concurrent request?4 GB per concurrent requestWhy are there regionalized prices?Our regional prices are based on the regional cost of infrastructure supporting our serverless productsHow do DBUs and concurrency work for model serving?Total queries/total time determines # of concurrent requests required per hour 1 DBU/hr provides 1 concurrent request/hr; minimum of 4 DBU/hr What is Model Execution time?Model Execution Time refers to the time required for running a machine learning model on Model Serving. To estimate execution time, you can check the latency chart on the endpoint page or conduct load testing. Feel free to contact our team for guidance on load testing.What is the minimum charge if Scale to Zero is not selected and there is no traffic ?If the 'scale to zero' is not selected, the minimum charge will depend on the minimum provisioned concurrency specified by the chosen concurrency range.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/erika-ehrli/#

Erika Ehrli - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingErika EhrliSenior Director of Product Marketing at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/don-scott/#

Don Scott - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDon ScottVP, New Product Development at Hitachi Solutions AmericaBack to speakersDon, is the VP of New Product Development at Hitachi Solutions. With 10 years in emerging technology, and a background in high-performance compute, he currently drives success for clients by leading the Empower Analytics Platform. Passionate about cloud solutions, Don's mission is to address historic labor shortages through automation in the data and AI space.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/nadine-farah

Nadine Farah - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingNadine FarahHead of Dev Rel at OnehouseBack to speakersNadine Farah is head of dev rel at Onehouse and an Apache Hudi contributor. She's passionate about bridging engineering, product & marketing to help drive product adoption. She previously lead Rockset's developer initiatives where she focused on building technical content to drive developer adoption for real-time analytics. At Bose, she contributed to the watchOS SDK & worked with partners to embrace spatial audio in the music and gaming industries.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/lindsay-mico

Lindsay Mico - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLindsay MicoHead of Data Science at Providence HealthBack to speakersLindsay Mico is the Head of Data Science for Providence, with a focus on enterprise scale AI solutions and cloud native architectures. Originally trained as a cognitive neuroscientist and statistician, he has worked across industries including natural resource management, telecom, and healthcare.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

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Explore the Lakehouse for Manufacturing Thumbnails Document Outline Attachments Layers Current Outline Item Previous Next Highlight All Match Case Match Diacritics Whole Words Color Size Color Thickness Opacity Presentation Mode Open Print Download Current View Go to First Page Go to Last Page Rotate Clockwise Rotate Counterclockwise Text Selection Tool Hand Tool Page Scrolling Vertical Scrolling Horizontal Scrolling Wrapped Scrolling No Spreads Odd Spreads Even Spreads Document Properties… Toggle Sidebar Find Previous Next Presentation Mode Open Print Download Current View FreeText Annotation Ink Annotation Tools Zoom Out Zoom In Automatic Zoom Actual Size Page Fit Page Width 50% 75% 100% 125% 150% 200% 300% 400% More Information Less Information Close Enter the password to open this PDF file: Cancel OK File name: - File size: - Title: - Author: - Subject: - Keywords: - Creation Date: - Modification Date: - Creator: - PDF Producer: - PDF Version: - Page Count: - Page Size: - Fast Web View: - Close Preparing document for printing… 0% Cancel

https://www.databricks.com/dataaisummit/speaker/craig-wiley

Craig Wiley - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingCraig WileySr. Director of Product, Lakehouse AI at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

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Diversità e inclusione | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio / 8 AM PT Addio, Data Warehouse. Ciao, Lakehouse. Partecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno. Registrati oraSoluzioniSoluzioni per settoreServizi finanziariSanità e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT   Scopri la Lakehouse for Manufacturing Scopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons  26–29 giugno 2023 Partecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perché Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWIl futuro dei dati è aperto a tuttiDiversità, equità e inclusione in DatabricksGuidati dai dati. Supportati dalle persone.La nostra missione è diversificare i Big Data... a partire dal nostro team. Crediamo che estrazioni, esperienze, prospettive e competenze diverse alimentino l'innovazione e consolidino i rapporti fra di noi e con i nostri clienti. Puntiamo a coltivare una cultura di appartenenza in cui tutti siano messi nelle condizioni di svolgere il loro lavoro nel modo migliore. Dalla garanzia di parità salariale a parità di lavoro, alla definizione di programmi che celebrano, educano e fanno crescere il nostro team, i concetti di Diversità, Equità e Inclusione (DEI) sono "intrecciati" in tutto ciò che facciamo.Posto di lavoro certificato per l'equità salariale Siamo orgogliosi di essere fra le prime sei organizzazioni certificate da Fair Pay Workplace. Nell'ambito del suo impegno a raggiungere la parità salariale, Databricks ha effettuato una rigorosa valutazione dei dati e dei processi retributivi, impegnandosi alla massima trasparenza con analisi continue dell'equità salariale.Gaingels e Flucas Ventures Il nostro impegno per la diversità, l'equità e l'inclusione abbraccia tutto il nostro team, dalle persone che lavorano con noi a quelle che investono su di noi. Per questo siamo fieri di collaborare con una serie di investitori di caratura mondiale, fra cui Gaingels e Flucas Ventures, specializzati nel finanziamento di aziende che dimostrano grande attenzione in ambito DEI.“Sappiamo che più sono i dati in nostro possesso, più approfondite sono le nostre informazioni. Lo stesso vale per diversità e inclusione: Databricks cresce includendo la più ampia varietà di estrazioni, esperienze e punti di vista”.— Ali Ghodsi, Cofondatore e CEO, DatabricksLe nostre comunitàCrediamo che mettere i nostri dipendenti nelle migliori condizioni di lavoro sia la chiave per sfruttare appieno il loro potenziale. I nostri vivaci Employee Resource Group (ERG) sono collettivi gestiti dai dipendenti che svolgono un ruolo chiave nel creare un ambiente inclusivo e favorevole in Databricks. Queste diverse comunità di dipendenti e partner creano spazi di interazione e svago, oltre ad aumentare la consapevolezza rispetto a questioni importanti.Queeries Network Veterans Network Black Employee Network Women’s Network LatinX Network Asian Employee Network Le nostre esperienze“In Databricks costruisco team dei quali vorrei far parte. Questo significa avere la sicurezza di essere me stessa e offrire la stessa comfort zone a tutti quelli che mi circondano. L'attenzione che mostriamo l'uno per l'altro e la nostra dedizione all'inclusione hanno un forte impatto sull'intera comunità”.— Stacy Kerkela, Director of EngineeringMaggiori informazioni“La rete LatinX di Databricks rafforza il mio senso di appartenenza alla comunità, una comunità aperta, perché gli Employee Resource Group di Databricks accolgono e formano tutte le persone, qualunque sia il loro background”.— Miguel Peralvo, Senior Solutions ArchitectMaggiori informazioni“Molte aziende sono attente a promuovere la diversità di genere, ma è bello far parte di un'azienda che compie azioni concrete per spostare l'ago della bilancia”.— Allie Emrich, Program Management, ProductMaggiori informazioniIniziative di inclusioneReportCollaborazioni con ColorStack e Rewriting the CodeIl nostro team di reclutamento universitario collabora con ColorStack e Rewriting the Code per aiutare più donne e più studenti neri e latinoamericani a fare carriera nel settore della tecnologia.Maggiori informazioniReportProgramma di mentoring Women in TechIn Databricks riconosciamo l'importanza di offrire opportunità di crescita e avanzamento professionale a comunità storicamente sottorappresentate.Maggiori informazioniReport2021 InHerSight AwardSiamo entusiasti di essere considerati una delle aziende di software che favorisce maggiormente il lavoro delle donne, dalle donne stesse. Visita il profilo di InHerSight per saperne di più.Maggiori informazioniCostruiamo il futuro dei dati insiemeLa nostra missione è semplificare e democratizzare dati e AI, e non possiamo riuscirci senza il tuo contributo.Scopri le opportunitàProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiPosizioni aperte in DatabricksMondoEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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Análise de dados e IA para orgãos governamentais | DatabricksSkip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio | 8h PT   Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWAnálise de dados e IA para orgãos governamentaisLibere a inovação para oferecer melhores serviços públicos por meio de dados e machine learningDa estratégia federal de dados à ordem executiva de IA, o governo federal dos EUA está apostando na modernização de seus recursos de análise e armazenamento de dados.A Databricks Lakehouse Platform permite que as agências federais liberem todo o potencial de seus dados para atingir seus objetivos de missão e atender melhor os cidadãos.Capacitação de orgãos governamentais para alavancar dados e IA para cumprir os objetivos da missãoUsado pelas principais agências do setor público+ qualquer outro cliente compatível com Apache Spark™Saiba como os líderes do setor estão usando o Databricks para melhorar a experiência dos cidadãos em todos os serviços públicosÚltimos posts de blog, webinars e estudos de casoPor que Databricks para o orgãos governamentais?Modernize sua análise de dados130 caracteres. Modernize sua pilha de tecnologia para melhorar a experiência de pacientes e médicos com o pipeline DNAQSeq mais rápido em escala.Alcance os resultados da missão de forma eficaz e eficiente130 caracteres. Modernize sua pilha de tecnologia para melhorar a experiência de pacientes e médicos com o pipeline DNAQSeq mais rápido em escala.Crie experiências melhores para os cidadãos130 caracteres. Modernize sua pilha de tecnologia para melhorar a experiência de pacientes e médicos com o pipeline DNAQSeq mais rápido em escala.Saiba maisConformidade extensa para aprovação rápida e fácil para operar (ATO)A Databricks obteve ATOs em regiões, redes e controles de conformidade que suportam seus objetivos de missãoNuvensC2S SC2S GovCloud Nuvem pública RedesPúblico NIPR SIPR JWICS Controles de conformidadeFedRAMP FedRAMP-High FISMA IL5 IL6 ICS-503 Como a Databricks impulsiona a inovação para o governo federalCuidados de saúdeMelhore a prestação e a qualidade dos serviços de saúde para os cidadãos com análises poderosas e uma visão de 360° dos pacientes. Patient 360  Otimização da cadeia de suprimentos  Gestão de seguros Genômica Descoberta e entrega de medicamentosDefesaAplique os benefícios da análise preditiva aos dados geoespaciais, de IoT e de vigilância para melhorar as operações e proteger o país.  Logística Manutenção preditiva  Vigilância e reconhecimento  Aplicação da lei e disponibilidade operacionalSegurança nacionalDetecte e evite atividades criminosas e ameaças em nível nacional com análises em tempo real e tomada de decisão orientada por dados.  Alfândega e proteção de fronteiras  Imigração e cidadania  Combate ao terrorismo  Gestão do auxílio emergencial federalAutoridade pública/comércioDetecte irregularidades proativamente usando machine learning para reduzir riscos e evitar atividades fraudulentas.  Fraude e cobrança fiscais  Gerenciamento de processos e operações  Gerenciamento de concessões  Customer 360EnergiaMelhore a gestão de energia com insights de dados que garantem resiliência e sustentabilidade energética.  Segurança da infraestrutura energética  Gestão de energia mais inteligente  Exploração de energia  Confiabilidade da rede elétricaComunidade de inteligênciaAproveite insights em tempo real para tomar decisões informadas que podem afetar a segurança dos nossos cidadãos e do mundo.  Detecção de ameaças  Neutralizar ataques cibernéticos  Vigilância e reconhecimento da inteligência  Análise de mídia socialRecursosHistória de clienteImpulsionando a transformação digital para colocar os pacientes em primeiro lugar no CMSPráticas recomendadas de governança de dados — Lições aprendidas com os centros de serviços Medicare e MedicaidLições aprendidas com a modernização da plataforma de análise de dados do USCISModernizar orça aérea com Big Data e IAWebinarsResposta rápida às operações hospitalares usando dados e IA durante a pandemia de COVID-19Análise geoespacial e IA no setor públicoArquitetura moderna de análise de dados para o governoMelhorar a detecção de ameaças com Big Data e IANotíciasAzure Databricks obtém autorização elevada FedRAMP no Microsoft Azure Government (MAG)Segurança de nível governamental na nuvem AWSAnálises unificadas para clientes do governoCapacitar a comunidade de inteligência dos EUA com análise de missão crítica e IADiscussões do SummitAutomatizar a ingestão e análise de dados do System-Wide Information Management (SWIM) da Federal Aviation Administration (FAA)Análise geoespacial em escala: Análise de padrões de movimento humano durante uma pandemiaTudo pronto para começar?Adoraríamos saber sobre seus objetivos de negócios. Nossa equipe de serviços fará todo o possível para ajudar sua empresa a ter sucesso. Experimente gratuitamenteEntre em contatoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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Privacy Notice | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesPrivacy NoticeThis Privacy Notice explains how Databricks, Inc. and its affiliates (“Databricks”, “we”, “our”, and “us”) collects, uses, shares and otherwise processes your personal information (also known as personal data) in connection with the use of Databricks websites and applications that link to this Privacy Notice (the “Sites”), our data processing platform products and services (the “Platform Services”) and in the usual course of business, such as in connection with our events, sales, and marketing activities (collectively, “Databricks Services”). 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This Privacy Notice does not apply to (i) the data that our Customers upload, submit or otherwise make available to the Platform Services and other data that we process on their behalf, as defined in our agreement with the Customer; (ii) any products, services, websites, or content that are offered by third parties or that have their own privacy notice; or (iii) personal information that we collect and process in connection with our recruitment activities, which is covered under our Applicant Privacy Notice.We recommend that you read this Privacy Notice in full to ensure that you are informed. However, if you only want to access a particular section of this Privacy Notice, you can click on the link below to go to that section.Information We Collect About YouHow We Use Your InformationHow We Share Your InformationInternational TransfersYour Choices and RightsAdditional Information for Certain JurisdictionsOther Important InformationChanges to this NoticeHow to Contact UsInformation We Collect About YouInformation that we collect from or about you includes information you provide, information we collect automatically, and information we receive from other sources.Information you provideWhen using our Databricks Services, we may collect certain information, such as your name, email address, phone number, postal address, job title, and company name. We may also collect other information that you provide through your interactions with us, for example if you request information about our Platform Services, interact with our sales team or contact customer support, complete a survey, provide feedback or post comments, register for an event, or take part in marketing activities. We may keep a record of your communications with us and other information you share during the course of the communications.When you create an account, for example, through our Sites or register to use our Platform Services, we may collect your personal information, such as your name and contact information. We may also collect credit card information if chosen by you as a payment method, which may be shared with our third party service providers, including for payment and billing purposes. Information we collect automatically We use standard automated data collection tools, such as cookies, web beacons, tracking pixels, tags, and similar tools, to collect information about how people use our Sites and interact with our emails.For example, when you visit our Sites we (or an authorized third party) may collect certain information from you or your device. This may include information about your computer or device (such as operating system, device identifier, browser language, and Internet Protocol (IP) address), and information about your activities on our Sites (such as how you came to our Sites, access times, the links you click on, and other statistical information). For example, your IP address may be used to derive general location information. We use this information to help us understand how you are using our Sites and how to better provide the Sites to you. We may also use web beacons and pixels in our emails. For example, we may place a pixel in our emails that notifies us when you click on a link in the email. We use these technologies to improve our communications. The types of data collection tools we use may change over time as technology evolves. You can learn more about our use of cookies and similar tools, as well as how to opt out of certain data collection, by visiting our Cookie Notice. When you use our Platform Services, we automatically collect information about how you are using the Platform Services (“Usage Data”). While most Usage Data is not personal information, it may include information about your account (such as User ID, email address, or Internet Protocol (IP) address) and information about your computer or device (such as browser type and operating system). It may also include information about your activities within the Platform Services, such as the pages or features you access or use, the time spent on those pages or features, search terms entered, commands executed, information about the types and size of files analyzed via the Platform Services, and other statistical information relating to your use of the Platform Services. 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https://www.databricks.com/dataaisummit/speaker/amrinder-singh-oberai/#

Amrinder Singh Oberai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAmrinder Singh OberaiEMR Migrations Lead at DatabricksBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

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Krishti Bikal - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingKrishti BikalSenior Executive - Director BI & Analytics at EmeraldBack to speakersKrishti is a Senior technical Executive at EmeraldX, where he is currently leading various Data Analytics projects. One of them is implementation of ThoughtSpot Everywhere for Emerald's Customer Hub. He has over 15 years of industry experience in Data Engineering and Analytics. He holds B. Tech in Mechanical Engineering from NIT Patna, India and Masters in MIS from University of Illinois, USA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/blog/2021/11/11/10-powerful-features-to-simplify-semi-structured-data-management-in-the-databricks-lakehouse.html

10 Powerful Features to Simplify Semi-structured Data Management in the Databricks Lakehouse - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. 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JSON data is very flexible, which makes it powerful, but also difficult to ingest and query. The biggest challenges include:It’s a tedious and fragile process to define a schema of the JSON file being ingested.The schema can change over time, and you need to be able to handle those changes automatically.Software does not always pick the correct schema for your data, and you may need to hint at the correct format. For example, the number 32 could be interpreted as either an integer or a long.Often data engineers have no control of upstream data sources generating the semi-structured data. For example, the column name may be upper or lower case but denotes the same column, or the data type sometimes changes, and you may not want to completely rewrite the already ingested data in Delta Lake.You may not want to do the upfront work of flattening out JSON documents and extracting every single column, and doing so may make the data very hard to use.Querying semi-structured data in SQL is hard. You need to be able to query this data in a manner that is easy to understand.In this blog and the accompanying notebook, we will show what built-in features make working with JSON simple at scale in the Databricks Lakehouse. Below is an incremental ETL architecture. The left-hand side represents continuous and scheduled ingest, and we will discuss how to do both types of ingest with Auto Loader. After the JSON file is ingested into a bronze Delta Lake table, we will discuss the features that make it easy to query complex and semi-structured data types that are common in JSON data.In the accompanying notebook, we used sales order data to demonstrate how to easily ingest JSON. The nested JSON sales order datasets get complex very quickly. Read Rise of the Data Lakehouse to explore why lakehouses are the data architecture of the future with the father of the data warehouse, Bill Inmon.Hassle-free JSON ingestion with Auto LoaderAuto Loader provides Python and Scala interfaces to ingest new data from a folder location in object storage (S3, ADLS, GCS) into a Delta Lake table. Auto Loader makes ingestion easy and hassle-free by enabling data ingestion into Delta Lake tables directly from object storage in either a continuous or scheduled way.Before discussing the general features of Auto Loader, let’s dig into the features that make ingesting the JSON extremely easy. Below is an example of how to ingest very complex JSON data. df = spark.readStream.format("cloudFiles") \ .option("cloudFiles.schemaLocation", schemaLocation) \ .option("cloudFiles.format", "json") \ .option("cloudFiles.inferColumnTypes", "true") \ .option("cloudFiles.schemaEvolutionMode", "addNewColumns") \ .option("cloudFiles.schemaHints", schemaHints) \ .load(landingZoneLocation) Flexibility and ease of defining the schema: In the code above, we use two features of Auto Loader to easily define the schema while giving guardrails for problematic data. The two useful features are cloudFiles.inferColumnTypes and cloudFiles.schemaHints. Let’s take a closer look at the definitions:Feature 1 - Use cloudFiles.inferColumnTypes for automatically inferring data types during the schema inference process: The default value for cloudFiles.inferColumnTypes is false because, in most cases, it is better to have the top-level columns be strings for schema evolution robustness and avoid issues such as numeric type mismatches(integers, longs, floats) during the schema evolution process.Feature 2 - Use cloudFiles.schemaHints for specifying the desired data type to complement schema inference: Schema hints are used only if you do not provide a schema to Auto Loader. You can use schema hints whether cloudFiles.inferColumnTypes is enabled or disabled. More details can be found here.In this use case (notebook), we actually set cloudFiles.inferColumnTypes to true since we want the columns and the complex data types to be inferred, instead of Auto Loader’s default inferred data type of string. Inferring most columns will give the fidelity of this complex JSON and provide flexibility for querying later. In addition, while inferring the column types is very convenient, we also know there are problematic columns ingested. This is where cloudFiles.schemaHints comes into play, working together with cloudFiles.inferColumnTypes. The combination of the two options allows for inferring most columns’ complex data types while specifying the desired data type (string in this example) for only two of the columns.Let’s take a closer look at the two problematic columns. From the semi-structured JSON data we use in the notebook, we have identified two columns of problematic data: “ordered_products.element.promotion_info” and “clicked_items”. Hence, we hint that they should come in as strings (see data snippets for one of the columns above: “ordered_products.element.promotion_info”). For these columns, we can easily query the semi-structured JSON in SQL, which we will discuss later. You can see that one of the hints is on a nested column inside an array, which makes this feature really functional on complex schemas!Feature 3 - Use Schema Evolution to handle schema changes over time make the ingest and data more resilient: Like schema inference, schema evolution is simple to implement with Auto Loader. All you have to do is set cloudFiles.schemaLocation, which saves the schema to that location in the object storage, and then the schema evolution can be accommodated over time. To clarify, schema evolution is when the schema of the ingested data changes and the schema of the Delta Lake table changes accordingly.For example, in the accompanying notebook, an extra column named fulfillment_days is added to the data ingested by Auto Loader. This column is identified by Auto Loader and applied automatically to the Delta Lake table. Per the documentation, you can change the schema evolution mode to your liking. Here is a quick overview of the supported modes for Auto Loader’s option cloudFiles.schemaEvolutionMode:addNewColumns: The default mode when a schema is not provided to Auto Loader. New columns are added to the schema. Existing columns do not evolve data types.failOnNewColumns: If Auto Loader detects a new column, the stream will fail. It will not restart unless the provided schema is updated or the offending data file is removed.rescue: The stream runs with the very first inferred or provided schema. Any data type changes or new columns are automatically saved in the rescued data column as _rescued_data in your stream’s schema. In this mode, your stream will not fail due to schema changes.none: The default mode when a schema is provided to Auto Loader. It does not evolve the schema. New columns are ignored, and data is not rescued unless the rescued data column is provided separately as an option.The example above (also in the notebook) does not include a schema, hence we use the default option .option("cloudFiles.schemaEvolutionMode", "addNewColumns") on readStream to accommodate schema evolution.Feature 4 - Use rescued data column to capture bad data in an extra column, so nothing is lost: The rescued data column is where all unparsed data is kept, which ensures that you never lose data during ETL. If data doesn’t adhere to the current schema and can’t go into its required column, the data won’t be lost with the rescued data column. In this use case (notebook), we did not use this option. To turn on this option, you can specify the following: .option("cloudFiles.schemaEvolutionMode", "rescue"). Please see more information here.Now that we have explored the Auto Loader features that make it great for JSON data and tackled challenges mentioned at the beginning, let’s look at some of the features that make it hassle-free for all ingest: df.writeStream \ .format("delta") \ .trigger(once=True) \ .option("mergeSchema", "true") \ .option("checkpointLocation", bronzeCheckPointLocation) \ .start(bronzeTableLocation) Feature 5 - Use Trigger Once and Trigger AvailableNow for continuous vs. scheduled ingest: While Auto Loader is an Apache Spark™ Structured Streaming source, it does not have to run continuously. You can use the trigger once option to turn it into a scheduled job that turns itself off when all files have been ingested. This comes in handy when you don’t have the need for continuously running ingest. Yet, it also gives you the ability to drop the cadence of the schedule over time and then eventually go to continuously running ingest without changing the code. In DBR 10.1 and later, we have introduced Trigger.AvailableNow, which provides the same data processing semantics as trigger once, but can also perform rate limiting to ensure that your data processing can scale to very large amounts of data.Feature 6 - Use Checkpoints to handle state: State is the information needed to start up where the ingestion process left off if the process is stopped. For example, with Auto Loader, the state would include the set of files already ingested. Checkpoints save the state if the ETL is stopped at any point, whether on purpose or due to failure. By leveraging checkpoints, Auto Loader can run continuously and also be a part of a periodic or scheduled job. In the example above, the checkpoint is saved in the option checkpointLocation . If the Auto Loader is terminated and then restarted, it will use the checkpoint to return to its latest state and will not reprocess files that have already been processed.Querying semi-structured and complex structured dataNow that we have our JSON data in a Delta Lake table, let's explore the powerful ways you can query semi-structured and complex structured data. Let’s tackle the last challenge of querying semi-structured data.Until this point, we have used Auto Loader to write a Delta Table to a particular location. We can access this table by location in SQL, but for readability, we point an external table to the location using the following SQL code. CREATE TABLE autoloaderBronzeTable LOCATION '${c.bronzeTablePath}'; Easily access top level and nested data in semi-structured JSON columns using syntax for casting values: SELECT fulfillment_days, fulfillment_days:picking, fulfillment_days:packing::double, fulfillment_days:shipping.days FROM autoloaderBronzeTable WHERE fulfillment_days IS NOT NULL When ingesting data, you may need to keep it in a JSON string, and some data may not be in the correct data type. In those cases, syntax in the above example makes querying parts of the semi-structured data simple and easy to read. To double click on this example, let’s look at data in the column filfillment_days, which is a JSON string column:Feature 7 - Use single colon (:) to extract the top-level of a JSON string column: For example, filfillment_days:picking returns the value 0.32 for the first row above.Feature 8 - Use Dot Notation to access nested fields: For example, fulfillment_days:shipping.days returns the value 3.7 for the first row above.Feature 9 - Use double colon (::) to specify the desired data type to return for casting value: For example, fulfillment_days:packing::double returns the double data type value 1.99 for the string value of packing for the first row above.Extracting values from semi-structured arrays even when the data is ill-formed: SELECT *, reduce(all_click_count_array, 0, (acc, value) -> acc + value) as sum FROM ( SELECT order_number, clicked_items:[*][1] as all_click_counts, from_json(clicked_items:[*][1], 'ARRAY<string>')::ARRAY<int> as all_click_count_array FROM autoloaderBronzeTable ) </int></string>Unfortunately, not all data comes to us in a usable structure. For example, the column clicked_items is a confusing array of arrays in which the count comes in as a string. Below is a snippet of the data in the column clicked_items:Feature 10 - Extracting Values From Arrays: Use an asterisk (*) to extract all values in a JSON array string. For the specific array indices, use a 0-based value. For example, SQL clicked_items:[*][1]returns the string value of ["54","85"].Casting complex array values: After extracting the correct values for the array of arrays, we can use from_json and ::ARRAY to cast the array into a format that can be summed using reduce. In the end, the first row returns the summed value of 139 (54 + 89). It’s pretty amazing how easily we can sum values from ill-formed JSON in SQL!Aggregations in SQL with complex structured data: Accessing complex structured data, as well as moving between structured and semi-structured data, has been available for quite some time in Databricks. SELECT order_date, ordered_products_explode.name as product_name, SUM(ordered_products_explode.qty) as quantity FROM ( SELECT DATE(from_unixtime(order_datetime)) as order_date, EXPLODE(ordered_products) as ordered_products_explode FROM autoloaderBronzeTable WHERE DATE(from_unixtime(order_datetime)) is not null ) GROUP BY order_date, ordered_products_explode.name ORDER BY order_date, ordered_products_explode.name In the SQL query above, we explored how to access and aggregate data from the complex structured data in the column ordered_products. To show the data complexity, below is an example of one row of the column ordered_products, and our goal here is to find the quantity of each product sold on a daily basis. As you can see, both the product and quantity are nested in an array.Accessing array elements as rows: Use explode on the ordered_products column so that each element is its own row, as seen below.Accessing nested fields: Use the dot notation to access nested fields in the same manner as semi-structured JSON. For example, ordered_products_explode.qty returns the value 1 for the first row above. We can then group and sum the quantities by date and the product name.Additional Resources: we have covered many topics on querying structured and semi-structured JSON data, but you can find more information here:Documentation on querying semi-structured JSON in SQL.A blog on working complex structured and semi-structured data. The specific use case is working with complex data while streaming.ConclusionAt Databricks, we strive to make the impossible possible and the hard easy. Auto Loader makes ingesting complex JSON use cases at scale easy and possible. The SQL syntax for semi-structured and complex data makes manipulating data easy. Let’s recap the 10 features:Feature 1 - Infer Column Types for inferring data types during schema inferenceFeature 2 - Schema Hints for specifying desired data types to complement schema inferenceFeature 3 - Schema Evolution for handling schema changes in ingested data over timeFeature 4 - Rescued Data Column for capturing bad data in an extra column, so nothing is lostFeature 5 - Trigger Once and Trigger AvailableNow for continuous and scheduled ingest for large amounts of dataFeature 6 - Checkpoints for handling the state of the ingestion processFeature 7 - Extract JSON Columns for accessing top-level columns in JSON fileFeature 8 - Dot Notation for accessing nested fieldsFeature 9 - Casting Values for converting values to specified data typesFeature 10 - Extracting Values From Arrays for accessing arrays and structs within arraysNow that you know how to ingest and query complex JSON with Auto Loader and SQL, we can’t wait to see what you build with them.Try the notebook Try Databricks for freeGet StartedRelated posts10 Powerful Features to Simplify Semi-structured Data Management in the Databricks LakehouseNovember 11, 2021 by John O'Dwyer and Emma Liu in Engineering Blog Hassle Free Data Ingestion Discover how Databricks simplifies semi-structured data ingestion into Delta Lake with detailed use cases, a demo, and live Q&A... See all Engineering Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/albert-hu

Albert Hu - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAlbert HuSenior Analytics Engineer at Rec RoomBack to speakersAlbert is a Senior Analytics Engineer at Rec Room, a social UGC app you can play on multiple platforms. In this role, he is responsible for building out the infrastructure to enable analysis, experimentation, and product features. Prior to Rec Room, Albert held various roles in both startups and Fortune 500 companies including Head of Analytics at Ribbon and Data Product roles at Walmart. He holds a B.A., Economics and Mathematics from Northwestern University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/kr/company/partners

파트너 | DatabricksSkip to main content플랫폼Databricks 레이크하우스 플랫폼Delta Lake데이터 거버넌스데이터 엔지니어링데이터 스트리밍데이터 웨어하우징데이터 공유머신 러닝데이터 사이언스가격Marketplace오픈 소스 기술보안 및 신뢰 센터웨비나 5월 18일 / 오전 8시(태평양 표준시) 안녕, 데이터 웨어하우스. 안녕하세요, 레이크하우스입니다. 데이터 레이크하우스가 최신 데이터 스택에 어떻게 부합하는지 이해하려면 참석하십시오. 지금 등록하세요솔루션산업별 솔루션금융 서비스의료 서비스 및 생명 공학제조커뮤니케이션, 미디어 및 엔터테인먼트공공 부문리테일모든 산업 보기사용 사례별 솔루션솔루션 액셀러레이터프로페셔널 서비스디지털 네이티브 비즈니스데이터 플랫폼 마이그레이션5월 9일 | 오전 8시(태평양 표준시)   제조업을 위한 레이크하우스 살펴보기 코닝이 수동 검사를 최소화하고 운송 비용을 절감하며 고객 만족도를 높이는 중요한 결정을 내리는 방법을 들어보십시오.지금 등록하세요학습관련 문서교육 및 인증데모리소스온라인 커뮤니티University Alliance이벤트Data + AI Summit블로그LabsBeacons2023년 6월 26일~29일 직접 참석하거나 키노트 라이브스트림을 시청하세요.지금 등록하기고객파트너클라우드 파트너AWSAzureGoogle CloudPartner Connect기술 및 데이터 파트너기술 파트너 프로그램데이터 파트너 프로그램Built on Databricks Partner Program컨설팅 & SI 파트너C&SI 파트너 프로그램파트너 솔루션클릭 몇 번만으로 검증된 파트너 솔루션과 연결됩니다.자세히회사Databricks 채용Databricks 팀이사회회사 블로그보도 자료Databricks 벤처수상 실적문의처Gartner가 Databricks를 2년 연속 리더로 선정한 이유 알아보기보고서 받기Databricks 이용해 보기데모 보기문의처로그인JUNE 26-29REGISTER NOWDatabricks 파트너Databricks는 세계 각지에 1200+여 곳의 파트너 업체를 보유하고 있으며, Databricks와 함께 레이크하우스 플랫폼을 이용하여 고객에게 데이터, 분석 및 AI 솔루션과 서비스를 제공합니다. 이러한 파트너 업체에서는 고객이 Databricks를 활용해 고객이 보유한 데이터와 AI 워크로드를 모두 통합하여 좀 더 의미 있는 인사이트를 확보하도록 돕습니다.“Databricks는 데이터 볼륨을 제공하고 Tableau는 빠른 시각화를 제공합니다. 이들 솔루션이 우리 플랫폼의 핵심에서 나란히 작동하며 우리 고객이 첨단 자율 주행 차량 기능을 제공하는 데 필요한 성능을 제공합니다."— Patrick McAuliffe, Lead Engineer, Incite클라우드 파트너Databricks는 AWS, Microsoft Azure, Google Cloud 및 Alibaba Cloud에서 수행되며 각 클라우드 서비스 제공자의 인프라, 데이터 및 AI 서비스에 깊이 있게 통합되어 있음기술 파트너기술 파트너는 자사 솔루션을 Databricks 솔루션과 통합하여 ETL, 데이터 수집, BI, ML 및 거버넌스 등에 보완적 기능 제공컨설팅 파트너컨설팅 파트너는 Databricks와 함께 고객이 데이터, 분석과 AI 이니셔티브 전략 수립, 구현 및 확장을 추진하도록 돕기 유리한 독보적인 위치를 점한 전문가파트너 되기Databricks 파트너는 당사와 협력하여 고객을 위해 혁신적인 솔루션을 구축하여 제공합니다. Databricks 파트너 프로그램에 참여하여 각종 전용 툴, 교육, 솔루션즈 액셀러레이터 및 GTM 프로그램을 활용하세요.자세히제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모제품플랫폼 개요가격오픈 소스 기술Databricks 이용해 보기데모학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티학습 및 지원관련 문서용어집교육 및 인증헬프 센터법적 고지온라인 커뮤니티솔루션산업 기준프로페셔널 서비스솔루션산업 기준프로페셔널 서비스회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처회사Databricks 소개Databricks 채용다양성 및 포용성회사 블로그문의처Databricks 채용 확인하기WorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark 및 Spark 로고는 Apache Software Foundation의 상표입니다.개인 정보 보호 고지|이용약관|귀하의 개인 정보 선택|귀하의 캘리포니아 프라이버시 권리

https://www.databricks.com/dataaisummit/speaker/scott-bell/#

Scott Bell - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingScott BellPrincipal Consultant and Databricks SME at RapidDataBack to speakersScott is currently a Principal Consultant & Databricks SME with RapidData focusing on the Azure Data Platforms, Data Architecture, Integration Engineering and Analytics. Previously, he was a senior consultant and UK&I Databricks SME at Avanade a top global partner with Databricks.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/glossary/neural-network

What is a Neural Network?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWNeural NetworkAll>Neural NetworkTry Databricks for freeGet StartedWhat is a Neural Network?A neural network is a computing model whose layered structure resembles the networked structure of neurons in the brain. It features interconnected processing elements called neurons that work together to produce an output function. Neural networks are made of input and output layers/dimensions, and in most cases, they also have a hidden layer consisting of units that transform the input into something that the output layer can use.Types of Neural Network Architectures:Neural networks, also known as Artificial Neural network use different deep learning algorithms. Here are some the most common types of neural networks:Feed-Forward Neural Network:This is the most basic and common type of architecture; here the information travels in only one direction from input to output. It consists of an input layer; an output layer and in between, we have some hidden layers. If the hidden layer is more than one then that network is called a deep neural network.Recurrent Neural Network (RNNs)This is a more complex type of network; this artificial neural network is commonly used in speech recognition and natural language processing (NLP). RNNs perform the same task for every element of a sequence, with the output being depended on the previous computations.Convolutional Neural Network (ConvNets or CNNs)A CNN has several layers through which data is filtered into categories. CNNs have proven to be very effective in areas such as image recognition, text language processing, and classification. A convolutional neural network is made of an input layer, an output layer and a hidden layer that includes multiple convolutional layers, pooling layers, fully connected layers, and normalization layers.There are at least a dozen other kinds of neural network such as symmetrically connected network: Boltzmann machine networks, Hopfield networks,and many other types. Choosing the right network depends on the data you have to train it with, as well as on the specific application you have in mind.Additional ResourcesA Convolutional Neural Network Implementation For Car ClassificationIntroduction to Neural NetworksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/stan-lin

Stan Lin - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingStan LinSenior Software Engineer at Microsoft CorporationBack to speakersTech lead at Microsoft, MSAI. Experience in large-scale machine learning, graph intelligence, performant web services and compliance. Building the large-scale ML platform powering Microsoft 365 knowledge mining, search and recommendation.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/blog/2021/05/26/introducing-databricks-unity-catalog-fine-grained-governance-for-data-and-ai-on-the-lakehouse.html

Introducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the Lakehouse - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the Lakehouseby Matei Zaharia, Todd Greenstein and Cyrielle SimeoneMay 26, 2021 in AnnouncementsShare this postUpdate: Unity Catalog is now generally available on AWS, Azure, and GCP.Data lake systems such as S3, ADLS, and GCS store the majority of data in today’s enterprises thanks to their scalability, low cost, and open interfaces. Over time, these systems have also become an attractive place to process data thanks to lakehouse technologies such as Delta Lake that enable ACID transactions and fast queries. However, one area where data lakes have remained harder to manage than traditional databases is governance; so far, these systems have only offered tools to manage permissions at the file level (e.g. S3 and ADLS ACLs), using cloud-specific concepts like IAM roles that are unfamiliar to most data professionals.That’s why we’re thrilled to announce our Unity Catalog, which brings fine-grained governance and security to lakehouse data using a familiar, open interface. Unity Catalog lets organizations manage fine-grained data permissions using standard ANSI SQL or a simple UI, enabling them to safely open their lakehouse for broad internal consumption. It works uniformly across clouds and data types. Finally, it goes beyond managing tables to govern other types of data assets, such as ML models and files. Thus, enterprises get a simple way to govern all their data and AI assets:What’s hard with data lake governance tools today?Although all cloud storage systems (e.g. S3, ADLS and GCS) offer security controls today, these tools are file-oriented and cloud-specific, both of which cause problems as organizations scale up. We’ve often seen customers run into four problems:Lack of fine-grained (row, column and view level) security: Cloud data lakes can generally only set permissions at the file or directory level, making it hard to share just a subset of a table with particular users. This makes it tedious to onboard enterprise users who should not have access to the whole table.Governance tied to physical data layout: Because governance controls are at the file level, data teams must carefully structure their data layout to support the desired policies. For example, a team might partition data into different directories by country and give access to each directory to different groups. But what should the team do when governance rules change? If different states inside one country adopt different data regulations, the organization may need to restructure all its data.Nonstandard, cloud-specific interfaces: Cloud governance APIs such as IAM are unfamiliar to data professionals (e.g., database administrators), and different across clouds. Today, enterprises increasingly have to store data in multiple clouds, (e.g., to satisfy privacy regulations), so they need to be able to manage data across clouds.No support for other asset types: Data lake governance APIs work for files in the lake, but modern enterprise workflows produce a wide range of other types of data assets. For example, SQL workflows often revolve around views, data science workloads produce ML models, and many workloads connect to data sources other than the lake (e.g., databases). In the modern compliance landscape, all of these assets need to be governed the same way if they contain sensitive data. Thus, data teams have to reimplement the same security policies in many different systems.Unity Catalog's approachUnity Catalog solves these problems by implementing a fine-grained approach to data governance based on open standards that works across data asset types and clouds. It is designed around four key principles:Fine-grained permissions: Unity Catalog can enforce permissions for data at the row, column or view level instead of the file level, so that you can always share just part of your data with a new user without copying it.An open, standard interface: Unity Catalog’s permission model is based on ANSI SQL, making it instantly familiar to any database professional. We’ve also built a UI to make governance easy for data stewards, and we’ve extended the SQL model to support attribute-based access control, allowing you to tag many objects with the same attribute (e.g., “PII data”) and apply one policy to all of them. Finally, the same SQL based interface can be used to manage ML models and external data sources.Central control: Unity Catalog can work across multiple Databricks workspaces, geographic regions and clouds, allowing you to manage all enterprise data centrally. This central position also enables it to track lineage and audit all accesses.Secure access from any platform: Although we love the Databricks platform, we know that many customers will also access the data from other platforms and that they’d like their governance rules to work across them. Unity Catalog enforces security permissions from any client that connects through JDBC/ODBC or through Delta Sharing, the open protocol we’ve launched to exchange large datasets between a wide range of platforms.Let’s look at how the Unity Catalog can be used to implement common governance tasks.Easily manage permissions using ANSI SQLUnity Catalog brings fine-grained centralized governance to all data assets across clouds through the open standard ANSI SQL Data Control Language (DCL). This means administrators can easily grant permission to arbitrary user-specific subsets of the data using familiar SQL -- no need to learn an arcane, cloud-specific interface. We’ve also added a powerful tagging feature that lets you control access to multiple data items at once based on attributes to further simplify governance at scale.Below are a few examples of how you can use SQL grant statements with the Unity Catalog to add permissions to existing data stored on your data lake.First, you can create tables in the catalog either from scratch or by pointing to existing data in a cloud storage system, such as S3, accessed with cloud-specific credentials: CREATE EXTERNAL TABLE iot_events LOCATION s3:/... WITH CREDENTIAL iot_iam_roleYou can now simply use SQL standard GRANT statements to set permissions, as in any database. Below is an example of how to grant permissions to iot_events to an entire group such as engineers, or to just the date and country columns to the marketing group: GRANT SELECT ON iot_events TO engineers GRANT SELECT(date, country) ON iot_events TO marketingThe Unity Catalog also understands SQL views. This allows you to create SQL views to aggregate data in a complex way. Here is how you can use View-Based Access Control to grant access to only an aggregate version of the data for business_analysts: CREATE VIEW aggregate_data AS SELECT date, country, COUNT(*) AS num_events FROM iot_events GROUP BY date, country GRANT SELECT ON aggregate_data TO business_analystsIn addition, the Unity Catalog allows you to set policies across many items at once using attributes (Attribute-Based Access Control), a powerful way to simplify governance at scale. For example, you can tag multiple columns as PII and manage access to all columns tagged as PII in a single rule: ALTER TABLE iot_events ADD ATTRIBUTE pii ON email ALTER TABLE users ADD ATTRIBUTE pii ON phone GRANT SELECT ON DATABASE iot_data HAVING ATTRIBUTE NOT IN (pii) TO product_managersFinally, the same attribute system lets you easily govern MLflow models and other objects in a consistent way with your raw data: GRANT EXECUTE ON MODELS HAVING ATTRIBUTE (eu_data) TO eu_product_managersDiscover and govern data assets in the UIUnity Catalog's UI makes it easy to discover, describe, audit and govern data assets in one place. Data stewards can set or review all permissions visually, and the catalog captures audit and lineage information that shows you how each data asset was produced and accessed. The UI is designed for collaboration so that data users can document each asset and see who uses it.and secure data access to meet compliance and privacy needs, directly on the lakehouse.Share data across organizations with Delta SharingEvery organization needs to share data with customers, partners and suppliers to collaborate. Unity Catalog implements the open source Delta Sharing standard to let you securely share data across organizations, regardless of which computing platform or cloud they run on (any Delta Sharing client can connect to the data).Open interfaces for easy accessUnity Catalog works with your existing catalogs, data, storage and computing systems so you can leverage your existing investments and build a future-proof governance model. It can mount existing data in Apache Hive Metastores or cloud storage systems such as S3, ADLS and GCS without moving it. It also connects with governance platforms like Privacera and Immuta to let you define custom workflows for managing access to data. Finally, we designed Unity Catalog so that you can also access it from computing platforms other than Databricks: ODBC/JDBC interfaces and high-throughput access via Delta Sharing allow you to securely query your data any computing system. Try Databricks for freeGet StartedRelated postsIntroducing Databricks Unity Catalog: Fine-grained Governance for Data and AI on the LakehouseMay 26, 2021 by Matei Zaharia, Todd Greenstein and Cyrielle Simeone in Announcements Update: Unity Catalog is now generally available on AWS, Azure, and GCP. Data lake systems such as S3, ADLS, and GCS store the... See all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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https://www.databricks.com/dataaisummit/events-policy/

Events Policy - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingEvents PolicyPaymentsIn-person conference tickets and both in-person and virtual training will be assessed a fee and must be purchased with a credit card. Payment will be accepted in US dollars only. All registration fees must be paid in full prior to attending the conference. You will receive a payment confirmation and receipt via email once your credit card is processed and payment is complete. In order to receive the prices listed online you must complete and submit the online registration form by midnight (PST) on the deadline date. Any registration completed online after midnight (PST) will be processed at the next deadline price. Promo CodesIf you have a promo code, you must apply it at the time of your registration. Only one (1) promo code can be applied per registration. Transfers, Cancellation, and RefundsSubstitutions/Registration Transfer Substitution requests can be processed in person onsite or via written request at [email protected]  If requested in writing, please provide the names and emails of both the original and substitute registrants with both parties copied in the email. All requests for substitutions must be received no later than 5:00 p.m. (Pacific) on June 23, 2023.   Onsite substitutions will incur a US $50 processing fee.   Cancellations The Databricks Registration Team must receive all cancellation requests in writing via email at [email protected] by June 21, 2023.   Payment Information Payment accepted in US dollars only.   Refunds All paid items (such as training or in person registration packages) will be refunded to the original form of payment.   We will issue a full refund, less a 10% fee, for written cancellation requests received on or before March 27, 2023 at 11:59 PM PT.  Cancellation requests received between March 28, 2023 and May 25, 2023 at 11:59 PM PT, will be issued a 50% refund, less a 10% cancellation fee.  No refunds will be offered for paid items after May 26, 2023.   Refunds will be processed 5 to 7 business days after the cancellation request has been processed and confirmed to the method of payment on the attendee record.  If you have not received a refund by July 1, 2023, please contact the Databricks Registration Team at [email protected]   Please note: Any requests to change the payment method used for a completed registration will incur a $50 change fee. If you need to make a change, please contact the Databricks Registration Team at: [email protected]  Databricks reserves the right to deny registration to any individual or entity for any reason, in Databricks’s sole discretion, including for past or present failure to meet Databricks’s standards of conduct (including, but not limited to, engaging in violent, illegal, threatening, or discriminatory conduct).    Payment terms are Net 30.  Payment must be received in full to print attendee badge on-site. Registration ConfirmationRegistration will be confirmed by email. You’ll receive a message as soon as payment has been received and your registration has been processed. Speakers & SessionsThe speakers listed on this website are leading professionals in their respective fields. Should a speaker be unable to attend the conference, all efforts will be made to replace him or her with one of comparable experience and qualifications. We are constantly working on improving the quality of our conference products. If the opportunity arises we may, at our discretion, add conference sessions and workshops to the posted line-up to enhance the schedule. Photo Release & Privacy InformationFrom time to time Databricks may choose to photograph and record certain portions of the conference and may capture conference participants. Databricks may choose such photographs and recordings in our promotional materials. By virtue of your attendance at Data + AI Summit you consent to, Databricks’ use of your likeness in such materials and you hereby waive “moral rights” in such photos, recordings, or other digital content. You agree that any personal data you provide us will be handled in accordance with this Event Policy and our Privacy Policy.   You may not record any sessions or sessions at Data + AI Summit without prior approval from Databricks. Terms of Use. Privacy Policy. Code of Conduct.   HomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/madalina-tanasie

Madalina Tanasie - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMadalina TanasieChief Technology Officer at CollibraBack to speakersAs Collibra’s Chief Technology Officer, Madalina oversees Software Engineering, Architecture, Production Engineering, Test Engineering and Security. With over 18 years of software engineering leadership experience, her expertise includes service oriented architecture, cloud-native distributed systems and product operations with a focus on engineering practices, scale and operational excellence.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/jp/learn

トレーニング | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT さようなら、データウェアハウス。こんにちは、レイクハウス。 データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。 今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)   製造業のためのレイクハウスを発見する コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日 直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOWトレーニングトレーニング、認定試験、イベント、ドキュメントなど、今すぐ役立つ Databricks のリソースをご紹介Databricks を使ってみる基本を学ぶDatabricks Lakehouse Platformは、データパイプラインの構築と実行、データサイエンスとアナリティクスのプロジェクトでのコラボレーション、機械学習モデルの構築とデプロイを簡単に行えるようにします。 以下のスタートアップガイドをご覧ください。Databricks のご利用は初めてですか？経験豊富なカスタマーサクセスエンジニアが Databricks についてご紹介いたします。Databricks オンボーディング Lakehouse Fundamentals Training Watch 4 short videos, take the quiz and get your badge to share on LinkedIn or your résumé Get startedデータサイエンスとエンジニアリングDatabricksアドミニストレーターSQL Analytics機械学習トレーニングDatabricks Academyでトレーニングを受けてください。 UC BerkeleyでApache Spark™研究プロジェクトを開始したチームから、データ分析をマスターする方法を学びます。Databricks アカデミー認定認定試験は、Databricks Lakehouse Platformと、高品質なプロジェクトを成功させるために必要な手法をどれだけ知っているかを評価します。 業界の認知度向上、競争力の強化、生産性の向上、成果、そして教育投資に対する具体的な指標を得ることができるのです。Databricks認定資格疑問点を解決するこれから始めるにあたって出てくるであろう疑問を明確にするために、以下の方法から選んでください：Databricksのテクニカルエキスパートにライブで質問するオンラインコミュニティDatabricks コミュニティで今話題になっているトピックとは？ボタンをクリックすると閲覧できます。コミュニティに参加する話題のトピックDatabricksDelta LakeSparkSQLPySparkAzureAWSGCPハンズオンのヘルプが必要ですか？サポート契約をお持ちの方、またはご興味のある方は、以下のオプションをご確認ください。 戦略的なビジネスガイダンス（カスタマーサクセスエンジニアまたはプロフェッショナルサービス契約）については、ワークスペース管理者に連絡して、Databricksのアカウントエグゼクティブに連絡してください。サポートオプションを確認するNotebook ギャラリー多様なテクノロジーやユースケースに活用できる Notebook の可能性の一部をご紹介。Notebook は、現在ご利用になっている Databricks 環境および、無料のコミュニティ版 Databricks の環境に容易にインポートできます。Databricks の Notebook ギャラリー →ドキュメントDatabricks の技術ドキュメントのサイトでは、ペルソナベースの環境に合わせた Databricks のデータサイエンスとエンジニアリング、機械学習、SQL の手順の説明およびリファレンスを提供しています。AWS 関連資料Azure 関連資料Google 関連資料Databricks のイベントとコミュニティDATA+AI サミット業界、研究機関、学術界のエキスパートによる基調講演、製品発表など、200 を超える技術セッションを視聴できます。詳しく見るグローバルイベントグローバル・地域別カンファレンス、製品のデモ、Web セミナー、パートナー主催のイベント、ミートアップなど、各種イベントをご用意しています。詳しく見るDATA+AI オンラインミートアップオンライン開催の Databricks Meetup では、世界中の Databricks ユーザーとの交流を通じて最新情報を入手できます。詳しく見るBeaconsデータと AI のコミュニティの充実に向けて尽力する Databricks Beacons のメンバーをご紹介します。詳しく見る大学との連携Databricks では、Databricks を教育に取り入れることを希望する大学・教育者向けに、リソースを無料で提供しています。詳しく見るData Brew 動画ポッドキャストData+AI をスペシャリストと探索Brook Wenig and Denny Lee動画シリーズテックトークとミートアップBrook Wenig and Denny LeeテックトークMLflow による ML ライフサイクル管理ジュール・ダムジテックトークDelta Lake 入門Denny LeeテックトークDelta Lake 上級編Denny LeeDatabricks Demo Hub （製品デモ）DATA+AI の研究Matei Zaharia共同創業者兼 CTODatabricksReynold Xin共同創業者兼チーフアーキテクトDatabricksスー・アン・ホンソフトウェアエンジニアDatabricksDatabricks の創業者、社員、研究者が、カリフォルニア大学バークレー校やスタンフォード校などの一流大学との共同研究を通じて執筆した最新のリサーチペーパーにアクセスできます。アクセスリサーチ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利

https://www.databricks.com/dataaisummit/speaker/don-bosco-durai

Don Bosco Durai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDon Bosco DuraiCofounder and CTO at PrivaceraBack to speakersBosco is an enterprise security thought leader. Bosco co-founded XASecure which reinvented security at scale for Big Data which later became Apache Ranger. Bosco is currently co-founder and CTO at Privacera addressing data security & access governance challenges in the Cloud. He is also actively involved in the Open-Source communities as a committer in open source projects like Apache Ranger, Ambari, and HAWQ.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/?itm_data=mainnav-promo-dais2022

Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI. Register NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you’re an engineering wizard, ML pro, SQL expert — or you want to learn how to build, train and deploy LLMs — you’ll be in good company. See all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI — and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer. SessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more. Explore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark™, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto/Trino, DuckDB and much more. You’ll also get a first look at new products and features in the Databricks Lakehouse Platform. Browse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party. Learn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at “birds of a feather” meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark™, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world See agendaDon’t miss this year’s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/company/partners/consulting-and-si/partner-solutions/capgemini-revenue-growth-management

Capgemini Revenue Growth Management | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWBrickbuilder SolutionRevenue Growth Management by CapgeminiIndustry-specific solution developed by Capgemini and powered by the Databricks Lakehouse Platform Get startedBuild a better recommendation engineIn today’s dynamic environment, knowing what a customer purchased three months ago does not always tell you what they will purchase tomorrow. To establish fine-grained and accurate demand-sensing patterns, you need to incorporate externalities like dynamic market data, indices and social media. Capgemini’s revenue growth management engine leverages the Databricks Lakehouse for Retail to rapidly perform analysis of invoice data, external market data, indices, news and web scraping data to explore patterns. This improves on all aspects of the selling and marketing cycle, including acquisition, conversion and retention. With Capgemini Revenue Growth Management, you can:Preconfigure a visual interface and filter to display revenue growthPre-populate PySpark code and notebooks within Databricks for migrationsUtilize frameworks for initial product backlog structure and model selection criteriaGet startedDeliver AI innovation faster with solution accelerators for popular industry use cases. See our full library of solutions ➞ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/rafi-kurlansik/#

Rafi Kurlansik - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRafi KurlansikLead Solutions Architect at DatabricksBack to speakersRafi is a Lead Solutions Architect at Databricks where he specializes in Data Science, Machine Learning and the Developer Experience. He has also helped many customers scale their R workloads with Spark. In his spare time he enjoys gardening with native plants, cooking up a storm, and long video game sessions with his three children.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/jeff-mroz/#

Jeff Mroz - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJeff MrozTechnical SME for Cloud and Big Data at Woolpert / US Army Corps of EngineersBack to speakersJeff Mroz is a Woolpert technical Cloud SME working for government clients on Azure cloud data modernization and architecture, CI/CD pipeline development, Geospatial Big Data and Lake House workflows, and cloud R&D projects in secure government clouds.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/greg-nelson/#

Greg Nelson - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGreg NelsonVP of Data Operations at Highmark HealthBack to speakersGreg Nelson, MMCi, CPHIMS, FACHE serves as the Vice President, of Data Operations and is a key member of the executive leadership team for the Enterprise Data and Analytics organization at Highmark Health. Before joining Highmark, Greg held leadership roles at Intermountain Healthcare and ECU Health (formerly Vidant Health.) Greg was also the founder and CEO of ThotWave, a healthcare analytics advisory firm specializing in helping organizations mature their analytics maturity. Greg serves as an expert for the International Institute for Analytics (IIA) and as adjunct faculty at Duke University, where he teaches advanced analytics to master’s level students in both the School of Nursing and the Fuqua School of Business. An author with over 200 papers and publications, Mr. Nelson is a regular speaker and keynote presenter at national and international events as well as is also an educator and futurist for industry and association events. As an analytics evangelist and futurist, Greg has brought his 20+ years of analytics advisory work to bear through a recently published book addressing the people and process sides of analytics entitled The Analytics Lifecycle Toolkit (Wiley, 2018). Through this pragmatic treatment of the analytics lifecycle, Greg speaks to both the practical and human-centeredness of analytics in a way that is accessible and useful for all. Mr. Nelson earned his bachelor’s degree in Psychology from the University of California, Santa Cruz, a Master of Management in Clinical Informatics from Duke University, and conducted Ph.D. level work (ABD) in Social and Cognitive Psychology and Quantitative Methods from the University of Georgia. You can connect with Greg on Twitter @gregorysnelson or LinkedIn at www.linkedin.com/in/gregorysnelson/Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/blog/category/platform/announcements

The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/roie-schwaber-cohen/#

Roie Schwaber-Cohen - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingRoie Schwaber-CohenStaff Developer Advocate at PineconeBack to speakersRoie Schwaber-Cohen is a staff developer advocate at Pinecone. He has 15 years of software engineering experience and has worked in a variety of startups across industries. Roie is a musician, playing piano and flute. He lives in Seattle with my wife and daughter, along with our two dogs and cat.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/it/company/awards-and-recognition

Premi e riconoscimenti | DatabricksSkip to main contentPiattaformaThe Databricks Lakehouse PlatformDelta LakeGovernance dei datiIngegneria dei datiStreaming di datiData warehouseCondivisione dei datiMachine LearningData SciencePrezziMarketplaceTecnologia open-sourceSecurity and Trust CenterWEBINAR 18 maggio / 8 AM PT Addio, Data Warehouse. Ciao, Lakehouse. Partecipa per capire come una data lakehouse si inserisce nel tuo stack di dati moderno. Registrati oraSoluzioniSoluzioni per settoreServizi finanziariSanità e bioscienzeIndustria manifatturieraComunicazioni, media e intrattenimentoSettore pubblicoretailVedi tutti i settoriSoluzioni per tipo di applicazioneAcceleratoriServizi professionaliAziende native digitaliMigrazione della piattaforma di dati9 maggio | 8am PT   Scopri la Lakehouse for Manufacturing Scopri come Corning sta prendendo decisioni critiche che riducono al minimo le ispezioni manuali, riducono i costi di spedizione e aumentano la soddisfazione dei clienti.Registrati oggi stessoFormazioneDocumentazioneFormazione e certificazioneDemoRisorseCommunity onlineUniversity AllianceEventiConvegno Dati + AIBlogLabsBeacons  26–29 giugno 2023 Partecipa di persona o sintonizzati per il live streaming del keynoteRegistratiClientiPartnerPartner cloudAWSAzureGoogle CloudPartner ConnectPartner per tecnologie e gestione dei datiProgramma Partner TecnologiciProgramma Data PartnerBuilt on Databricks Partner ProgramPartner di consulenza e SIProgramma partner consulenti e integratori (C&SI)Soluzioni dei partnerConnettiti con soluzioni validate dei nostri partner in pochi clic.RegistratiChi siamoLavorare in DatabricksIl nostro teamConsiglio direttivoBlog aziendaleSala stampaDatabricks VenturesPremi e riconoscimentiContattiScopri perché Gartner ha nominato Databricks fra le aziende leader per il secondo anno consecutivoRichiedi il reportProva DatabricksGuarda le demoContattiAccediJUNE 26-29REGISTER NOWPremi e riconoscimentiScopri i riconoscimenti che Databricks ha ricevuto dai leader di settore.Leader nel 2022 Magic Quadrant for Cloud Database Management Systems2022 Customer Choice Award for Cloud Database Management SystemsLeader nel 2021 Magic Quadrant for Cloud Database Management SystemsLeader nel 2021 Magic Quadrant for Data Science and Machine LearningLakehouse — Hype Cycle for Data Management, 2022Aziende da tenere d'occhio nel 2023Le aziende più innovative nella data scienceThe Cloud 100The AI 50Le migliori startup americane in cui lavorareLe migliori aziende tecnologiche in cui lavorareLe migliori aziende in cui lavorare nella Baia di San FranciscoLe migliori aziende in cui lavorare per i millennialCNBC Disruptor 50Le migliori aziende in cui lavorare nel 2022Pronto per saperne di più?Vorremmo conoscere i tuoi obiettivi aziendali e come il nostro team di servizi potrebbe aiutarti a realizzarli.Prova Databricks gratisProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoProdottoPanoramica della piattaformaPrezziTecnologia open-sourceProva DatabricksDemoFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineFormazione e supportoDocumentazioneGlossaryFormazione e certificazioneHelp CenterLegaleCommunity onlineSoluzioniPer settoreServizi professionaliSoluzioniPer settoreServizi professionaliChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiChi siamoChi siamoLavorare in DatabricksDiversità e inclusioneBlog aziendaleContattiPosizioni aperte in DatabricksMondoEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Informativa sulla privacy|Condizioni d'uso|Le vostre scelte sulla privacy|I vostri diritti di privacy in California

https://www.databricks.com/blog/2021/08/06/5-key-steps-to-successfully-migrate-from-hadoop-to-the-lakehouse-architecture.html

5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architecture - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic Sector5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse Architectureby Harsh NarulaAugust 6, 2021 in Data StrategyShare this postThe decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision. In a previous blog, we dug into the reasons why every organization must re-evaluate its relationship with Hadoop. Once stakeholders from technology, data, and the business make the decision to move the enterprise off of Hadoop, there are several considerations that need to be taken into account before starting the actual transition. In this blog, we’ll specifically focus on the actual migration process itself. You’ll learn about the key steps for a successful migration and the role the lakehouse architecture plays in sparking the next wave of data-driven innovation.The migration stepsLet's call it like it is. Migrations are never easy. However, migrations can be structured to minimize adverse impact, ensure business continuity and manage costs effectively. To do this, we suggest breaking your migration off of Hadoop down into these five key steps:AdministrationData MigrationData ProcessingSecurity and GovernanceSQL and BI LayerStep 1: AdministrationLet’s review some of the essential concepts in Hadoop from an administration perspective, and how they compare and contrast with Databricks.Hadoop is essentially a monolithic distributed storage and compute platform. It consists of multiple nodes and servers, each with their own storage, CPU and memory. Work is distributed across all these nodes. Resource Management is done via YARN, which attempts best efforts to ensure that workloads get their share of compute.Hadoop also consists of metadata information. There is a Hive metastore, which contains structured information around your assets that are stored in HDFS. You can leverage Sentry or Ranger for controlling access to the data. From a data access perspective, users and applications can either access data directly through HDFS (or the corresponding CLI/API’s) or via a SQL type interface. The SQL interface, in turn, can be over a JDBC/ODBC connection using Hive for generic SQL (or in some cases ETL Scripts) or Hive on Impala or Tez for interactive queries. Hadoop also provides an HBase API and related data source services. More on the Hadoop ecosystem here.Next, let’s discuss how these services are mapped to or dealt with in the  Databricks Lakehouse Platform. In Databricks, one of the first differences to note is that you’re looking at multiple clusters in a Databricks environment. Each cluster could be used for a specific use case, a specific project, business unit, team or development group. More importantly, these clusters are meant to be ephemeral. For job clusters, the clusters’ life span is meant to last for the duration of the workflow. It will execute the workflow, and once it’s complete, the environment is torn down automatically. Likewise, if you think of an interactive use case, where you have a compute environment that’s shared across developers, this environment can be spun up at the beginning of the workday, with developers running their code throughout the day. During periods of inactivity, Databricks will automatically tear it down via the (configurable) auto-terminate functionality that’s built into the platform.Unlike Hadoop, Databricks does not provide data storage services like HBase or SOLR. Your data resides in your file storage, within object storage. A lot of the services like HBase or SOLR have alternatives or equivalent technology offerings in the cloud. It might be a cloud-native or an ISV solution.As you can see in the diagram above, each cluster node in Databricks corresponds to either Spark driver or a worker. The key thing here is that the different Databricks clusters are completely isolated from each other. This allows you to ensure that strict SLAs can be met for specific projects and use cases. You can truly isolate streaming or real-time use cases from other, batch oriented workloads, and you don’t have to worry about manually isolating long running jobs that could hog cluster resources for a long time. You can just spin up new clusters as compute for different use cases. Databricks also decouples storage from compute, and allows you to leverage existing cloud storage such as AWS S3, Azure Blob Storage and Azure Data Lake Store (ADLS).Databricks also has a default managed Hive metastore, which stores structured information about data assets that reside in cloud storage. It also supports using an external metastore, such as AWS Glue, Azure SQL Server or Azure Purview. You can also specify security control such as Table ACLs within Databricks, as well as object storage permissions.When it comes to data access, Databricks offer similar capabilities to Hadoop in terms of how your users interact with the data. Data stored in cloud storage, can be accessed through multiple paths in the Databricks environment. Users can use SQL Endpoints and Databricks SQL for interactive queries and analytics. They can also use the Databricks notebooks for Data Engineering and Machine Learning capabilities on the data stored in cloud storage. HBase in Hadoop maps to Azure CosmosDB, or AWS DynamoDB/Keyspaces, which can be leveraged as a serving layer for downstream applications.Step 2:  Data migrationComing from a Hadoop background, I’ll assume most of the audience would already be familiar with HDFS. HDFS is the storage file system used with Hadoop deployments that leverages disks on the nodes of the Hadoop cluster. So, when you scale HDFS, you need to add capacity to the cluster as a whole (i.e. you need to scale compute and storage together). If this involves procurement and installation of additional hardware, there can be a significant amount of time and effort involved.In the cloud, you have nearly limitless storage capacity in the form of cloud storage such as AWS S3, Azure Data Lake Storage or Blob Storage or Google Storage. There are no maintenance or health checks needed, and it offers built-in redundancy and high levels of durability and availability from the moment it is deployed. We recommend using native cloud services to migrate your data, and to ease the migration there are several partners/ISVs.So, how do you get started? The most commonly recommended route is to start with a dual ingestion strategy (i.e. add a feed that uploads data into cloud storage in addition to your on-premise environment). This allows you to get started with new use cases (that leverage new data) in the cloud without impacting your existing setup. If you’re looking for buy-in from other groups within the organization, you can position this as a backup strategy to begin with. HDFS traditionally has been a challenge to back up due to the sheer size and effort involved, so backing up data into the cloud can be a productive initiative anyway.In most cases, you can leverage existing data delivery tools to fork the feed and write not just to Hadoop but to cloud storage as well. For example, if you’re using tools/frameworks like Informatica and Talend to process and write data to Hadoop, it’s very easy to add the additional step and have them write to cloud storage. Once the data is in the cloud, there are many ways to work with that data.In terms of data direction, the data either be pulled from on-premise to the cloud, or pushed to the cloud from on-premise. Some of the tools that can be leveraged to push the data into the cloud are cloud native solutions (Azure Data Box, AWS Snow Family, etc.), DistCP (a Hadoop tool), other third party tools, as well as any in-house frameworks. The push option is usually easier in terms of getting the required approvals from the security teams.For pulling the data to the cloud, you can use Spark/Kafka Streaming or Batch ingestion pipelines that are triggered from the cloud. For batch, you can either ingest files directly or use JDBC connectors to connect to the relevant upstream technology platforms and pull the data. There are, of course, third party tools available for this as well. The push option is the more widely accepted and understood of the two, so let’s dive a little bit deeper into the pull approach.The first thing you’ll need is to set up connectivity between your on-premises environment and the cloud. This can be achieved with an internet connection and a gateway. You can also leverage dedicated connectivity options such as AWS Direct Connect, Azure ExpressRoute, etc. In some cases, if your organization is not new to the cloud, this may have already been set up so you can reuse it for your Hadoop migration project.Another consideration is the security within the Hadoop environment. If it is a Kerberized environment, it can be accommodated from the Databricks side. You can configure Databricks initialization scripts that run on cluster startup, install and configure the necessary kerberos client, access the krb5.conf and keytab files, which are stored in a cloud storage location, and ultimately execute the kinit() function, which will allow the Databricks cluster to interact directly with your Hadoop environment.Finally, you will also need an external shared metastore. While Databricks does have a metastore service that is deployed by default, it also supports using an external one. The external metastore will be shared by Hadoop and Databricks, and can be deployed either on-premises (in your Hadoop environment) or the cloud. For example, if you have existing ETL processes running in Hadoop and you cannot migrate them to Databricks yet, you can leverage this setup with the existing on-premises metastore, to have Databricks consume the final curated dataset from Hadoop.Step 3: Data ProcessingThe main thing to keep in mind is that from a data processing perspective, everything in Databricks leverages Apache Spark. All Hadoop programming languages, such as MapReduce, Pig, Hive QL and Java, can be converted to run on Spark, whether it be via Pyspark, Scala, Spark SQL or even R. With regards to the code and IDE, both Apache Zeppelin and Jupyter notebooks can be converted to Databricks notebooks, but it’s a bit easier to import Jupyter notebooks. Zeppelin notebooks will need to be converted to Jupyter or Ipython before they can be imported. If your data science team would like to continue to code in Zeppelin or Jupyter, they can use Databricks Connect, which allows you to leverage your local IDE (Jupyter, Zeppelin or even IntelliJ, VScode, RStudio, etc.) to run code on Databricks.When it comes to migrating Apache Spark™ jobs, the biggest consideration is Spark versions. Your on-premises Hadoop cluster may be running an older version of Spark, and you can use the Spark migration guide to identify what changes were made to see any impacts on your code. Another area to consider is converting RDDs to dataframes. RDDs were commonly used with Spark versions up to 2.x, and while they can still be used with Spark 3.x, doing so can prevent you from leveraging the full capabilities of the Spark optimizer. We recommend that you change your RDDs to dataframes wherever possible.Last but not least, one of the common gotchas we’ve come across with customers during migration is hard-coded references to the local Hadoop environment. These will, of course, need to be updated, without which the code will break in the new setup.Next, let’s talk about converting non-Spark workloads, which for the most part involve rewriting code. For MapReduce, in some cases, if you’re using shared logic in the form of a Java library, the code can be leveraged by Spark. However, you may still need to re-write some parts of the code to run in a Spark environment as opposed to MapReduce. Sqoop is relatively easy to migrate since in the new environments you’re running a set of Spark commands(as opposed to MapReduce commands) using a JDBC source. You can specify parameters in Spark code in the same way that you specify them in Sqoop. For Flume, most of the use cases we’ve seen are around consuming data from Kafka and writing to HDFS. This is a task that can be easily accomplished using Spark streaming. The main task with migrating Flume is that you have to convert the config file-based approach into a more programmatic approach in Spark. Lastly, we have Nifi, which is mostly used outside Hadoop, mostly as a drag and drop, self-service ingestion tool. Nifi can be leveraged in the cloud as well, but we see many customers using the opportunity to migrate to the cloud to replace Nifi with other, newer tools available in the cloud.Migrating HiveQL is perhaps the easiest task of all. There is a high degree of compatibility between Hive and Spark SQL, and most queries should be able to run on Spark SQL as-is. There are some minor changes in DDL between HiveQL and Spark SQL, such as the fact that Spark SQL uses the “USING” clause vs HiveQL’s “FORMAT” clause. We do recommend changing the code to use the Spark SQL format, as it allows the optimizer to prepare the best possible execution plan for your code in Databricks. You can still leverage Hive Serdes and UDFs, which makes life even easier when it comes to migrating HiveQL to Databricks.With respect to workflow orchestration, you have to consider potential changes to how your jobs will be submitted. You can continue to leverage Spark submit semantics, but there are also other, faster and more seamlessly integrated options available. You can leverage Databricks jobs and Delta Live Tables for code-free ETL to replace Oozie jobs, and define end-to-end data pipelines within Databricks. For workflows involving external processing dependencies, you’ll have to create the equivalent workflows/pipelines in technologies like Apache Airflow, Azure Data Factory, etc. for automation/scheduling. With Databricks’ REST APIs, nearly any scheduling platform can be integrated and configured to work with Databricks.There is also an automated tool called MLens (created by KnowledgeLens), which can help migrate your workloads from Hadoop to Databricks. MLens can help migrate PySpark code and HiveQL, including translation of some of the Hive specifics into Spark SQL so that you can take advantage of the full functionality and performance benefits of the Spark SQL optimizer. They are also planning to soon support migrating Oozie workflows to Airflow, Azure Data Factory, etc.Step 4: Security and governanceLet’s take a look at security and governance. In the Hadoop world, we have LDAP integration for connectivity to admin consoles like Ambari or Cloudera Manager, or even Impala or Solr. Hadoop also has Kerberos, which is used for authentication with other services. From an authorization perspective, Ranger and Sentry are the most commonly used tools.With Databricks, Single Sign On (SSO) integration is available with any Identity Provider that supports SAML 2.0. This includes Azure Active Directory, Google Workspace SSO, AWS SSO and Microsoft Active Directory. For Authorization, Databricks provides ACLs (Access Control Lists) for Databricks objects, which allows you to set permissions on entities like notebooks, jobs, clusters. For data permissions and access control, you can define table ACLs and views to limit column and row access, as well as leverage something like credential passthrough, with which Databricks passes on your workspace login credentials to the storage layer (S3, ADLS, Blob Storage.) to determine if you are authorized to access the data. If you need capabilities like attribute-based controls or data masking, you can leverage partner tools like Immuta and Privacera. From an enterprise governance perspective, you can connect Databricks to an enterprise data catalog such as AWS Glue, Informatica Data Catalog, Alation and Collibra.Step 5: SQL & BI layerIn Hadoop, as discussed earlier, you have Hive and Impala as interfaces to do ETL as well as ad-hoc queries and analytics. In Databricks, you have similar capabilities via Databricks SQL. Databricks SQL also offers extreme performance via the Delta engine, as well as support for high-concurrency use cases with auto-scaling clusters. Delta engine also includes Photon, which is a new MPP engine built from scratch in C++ and is vectorized to exploit both data level and instruction-level parallelism.Databricks provides native integration with BI tools such as Tableau, PowerBI, Qlik andlooker, as well as highly-optimized JDBC/ODBC connectors that can be leveraged by those tools. The new JDBC/ODBC drivers have a very small overhead (¼ sec) and a 50% higher transfer rate using Apache Arrow, as well as several metadata operations that support significantly faster metadata retrieval operations. Databricks also supports SSO for PowerBI, with support for SSO with other BI/dashboarding tools coming soon.Databricks has a built-in SQL UX in addition to the notebook experience mentioned above, which gives your SQL users their own lens with a SQL workbench, as well as light dashboarding and alerting capabilities. This allows for SQL-based data transformations and exploratory analytics on data within the data lake, without the need to move it downstream to a data warehouse or other platforms.Next stepsAs you think about your migration journey to a modern cloud architecture like the lakehouse architecture, here are two things to remember:Remember to bring the key business stakeholders along on the journey. This is as much of a technology decision as it is a business decision and you need your business stakeholders bought into the journey and its end state.Also, remember you’re not alone, and there are skilled resources across Databricks and our partners who have done this enough to build out repeatable best practices, saving organizations, time, money, resources, and reducing overall stress.Download the Hadoop to Databricks Technical Migration guide for step-by-step guidance, notebooks, and code to begin your migration.To learn more about how Databricks increases business value and start planning your migration off of Hadoop, visit databricks.com/migration.Migration Guide: Hadoop to Databricks Unlock the full potential of your data with this self-guided playbook.Download NowTry Databricks for freeGet StartedRelated posts5 Key Steps to Successfully Migrate From Hadoop to the Lakehouse ArchitectureAugust 6, 2021 by Harsh Narula in Data Strategy The decision to migrate from Hadoop to a modern cloud-based architecture like the lakehouse architecture is a business decision, not a technology decision... See all Data Strategy postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/jp/events

Databricks のイベント | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT さようなら、データウェアハウス。こんにちは、レイクハウス。 データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。 今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)   製造業のためのレイクハウスを発見する コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日 直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOWDatabricks のイベント今後開催される Databricks のミートアップ、Web セミナー、カンファレンスなどをご紹介します。Data + AI サミット 20236月26日～29日ライブ配信される基調講演や一部のセッションは、対面またはオンラインでの参加をお選びいただけます。ご登録Loading...Browse All Upcoming Events製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利

https://www.databricks.com/fr/product/delta-lake-on-databricks

Delta Lake sur Databricks – Planifiez une démo dès maintenant !Skip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT   Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWDelta LakeFiabilité, sécurité et performance de votre data lakeEssai gratuitregarder une démoQu'est-ce que Delta Lake ?Delta Lake est une couche de stockage au format ouvert qui offre fiabilité, sécurité et performances à votre data lake, pour les opérations de streaming mais aussi de batch. En remplaçant les silos par un emplacement unique dédié aux données structurées, semi-structurées et non structurées, Delta Lake constitue la base d'un lake house rentable et hautement évolutif.Des données fiables et de haute qualitéProposez une source de vérité unique et fiable pour toutes vos données, y compris pour les flux en temps réel. Vos équipes data travailleront ainsi toujours avec les bases les plus récentes. Grâce à la prise en charge des transactions ACID et à la validation des schémas, Delta Lake offre la fiabilité qui manque aux data lakes traditionnels. Cela vous permet de déployer des insights fiables dans toute votre organisation et de lancer des analyses et d'autres projets liés aux données directement depuis votre data lake, dans un temps jusqu'à 50 fois plus court.Partage de données ouvert et sécuriséDelta Sharing est le premier protocole ouvert pour le partage sécurisé des données. Il permet d'échanger facilement des données avec d'autres organisations, quel que soit l'endroit où elles se trouvent. L'intégration native avec le Unity Catalog vous permet de gérer et d'auditer les données partagées dans toutes les organisations, de façon centralisée. Cela vous permet également de partager en toute confiance des actifs de données avec vos fournisseurs et partenaires pour une meilleure coordination de votre activité, tout en répondant aux critères de sécurité et de conformité. Les intégrations avec les principaux outils et plateformes facilitent en outre la visualisation, l'interrogation, l'enrichissement et le contrôle des données partagées à partir des outils de votre choix.Des performances rapides comme l'éclairBâti sur le moteur Apache Spark™, Delta Lake offre des performances exceptionnelles en termes de vitesse et d'échelle. Grâce à des fonctionnalités qui optimisent ses performances comme l'indexation, Delta Lake permet à ses clients de traiter des charges ETL avec une vitesse d'exécution jusqu'à 48 fois supérieure.Ouvert et agileToutes les données de Delta Lake sont stockées au format ouvert Apache Parquet. Elles sont donc lisibles par n'importe quel lecteur adapté. Les API sont ouvertes et compatibles avec Apache Spark. Avec Delta Lake pour Databricks, vous accédez à un vaste écosystème open source, évitant ainsi tout verrouillage des données dans des formats propriétaires.Data engineering automatisé et fiableSimplifiez votre data engineering avec Delta Live Tables. Ce framework vous permet de construire et de gérer facilement des pipelines de données afin d'obtenir des données fraîches et de grande qualité sur Delta Lake. En aidant les équipes de data engineering à simplifier le développement et la gestion de l'ETL, grâce à la création de pipelines déclaratifs, à l'amélioration de la fiabilité des données et la mise en place d'opérations de production à l'échelle du Cloud, Delta Live Tables facilite la construction des fondations de Lakehouse.Sécurité et gouvernance à l'échelleDelta Lake réduit les risques grâce à une gouvernance des données reposant sur la finesse des contrôles d'accès, ce qui n'est en principe pas possible avec les data lakes. Vous pouvez mettre à jour rapidement et avec précision les données de votre data lake pour vous conformer à des réglementations telles que le RGPD, et maintenir une meilleure gouvernance des données grâce à la journalisation des audits. Ces fonctionnalités sont nativement intégrées et améliorées pour Databricks dans le cadre du Unity Catalog, le premier catalogue de données multicloud pour le Lakehouse.Cas d’utilisationLa BI sur vos donnéesMettez à disposition de vos analystes de nouvelles données en temps réel et obtenez des insights immédiats sur votre entreprise grâce à des tâches de Business Intelligence directement exécutées sur votre datalake. Delta Lake vous permet d'exploiter une architecture lakehouse multicloud qui offre des performances d'entreposage de données à des coûts proches de ceux des data lakes, pour un rapport prix / performance jusqu'à quatre fois meilleur pour les tâches SQL que les data warehouses classiques dans le Cloud.En savoir plusUnifier batch et streamingExécutez des opérations de streaming et de batch sur une architecture simplifiée, en évitant les systèmes complexes et redondants, ainsi que les difficultés opérationnelles. Dans Delta Lake, une table est à la fois une table batch mais aussi une source de streaming et un puits de données. L'ingestion de données en streaming, le remplissage historique par batch et les requêtes interactives fonctionnent sans aucun effort supplémentaire, s'intégrant directement à Spark Structured Streaming.Répondre aux exigences réglementairesDelta Lake élimine les problèmes liés à l'ingestion de données erronées, à la suppression des données pour des raisons de conformité et aux changements dans la capture de données modifiées (Change Data Capture). Grâce à la prise en charge des transactions ACID dans votre data lake, Delta Lake garantit que chaque opération est entièrement menée à bien ou abandonnée en vue de nouvelles tentatives ultérieures, sans nécessiter la création de nouveaux pipelines de données. D'autre part, Delta Lake enregistre toutes les transactions précédentes sur votre data lake, facilitant ainsi l'accès aux versions antérieures de vos données pour répondre de manière fiable aux normes de conformité telles que le RGPD et le CCPA.Réseau d'ingestion de donnéesDes connecteurs natifs pour faciliter une ingestion fiable et rapide des données dans Delta Lake, depuis tous vos stockages de fichiers, applications et bases de données.Clients« Databricks nous a fourni les analyses, les délais de mise sur le marché et le coup de pouce opérationnel dont nous avions besoin pour répondre aux nouvelles exigences du secteur de la santé. » – Peter James, Architecte en chef, Healthdirect AustraliaEn savoir plus« En exploitant Databricks et Delta Lake, nous avons déjà pu démocratiser les données à l'échelle, tout en réduisant de 60 % le coût d'exécution des tâches de production, ce qui nous fait économiser des millions de dollars. » - Steve Pulec, Directeur technique, YipitDataEn savoir plus« »Delta Lake offre des fonctionnalités ACID qui simplifient les opérations de pipeline de données afin d'améliorer la fiabilité et la cohérence des données. Parallèlement, des fonctionnalités telles que la mise en cache et l'indexation automatique permettent un accès efficace et performant aux données. » - Lara Minor, Senior Enterprise Data Manager, Columbia SportswearEn savoir plus« Delta Lake a créé une approche simplifiée de la gestion des pipelines de données. Nous avons ainsi pu réduire les coûts opérationnels tout en accélérant la production d'analyses et les processus de data science. » - Parijat Dey, Vice-président adjoint, en charge de la transformation numérique et de la technologie, Viacom18En savoir plusRessources Toutes les ressources dont vous avez besoin. Réunies au même endroit. Explorez notre bibliothèque de ressources : vous y trouverez des ebooks et des vidéos sur les atouts du data engineering sur Databricks. Explorer les ressourcesEbooksLe Grand Livre des cas d'usage du data engineeringDonnées, analyses et gouvernance de l'IADécouvrez les Fondamentaux de la gestion des donnéesCréer le Data Lakehouse par Bill Inmon, père du data warehouseConférences et formations technologiquesDémarrer avec Delta Lake – Série de Tech TalksWebinairesLe bon, la brute et le truandPlongez dans le lakehouse avec Delta LakePrêt à vous lancer ?ESSAYER GRATUITEMENT DATABRICKSDocumentation Delta LakeProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie

https://www.databricks.com/product/spark

Spark on Databricks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSpark on DatabricksThe best platform to run your Spark workloads, from the original creators of Apache Spark™Simplicity, best-in-class operational excellence and price/performance benefits make the Databricks Lakehouse Platform the best place to run your Apache Spark™ workloadsBest-in-class operational excellenceWe help thousands of customers launch millions of VMs every day to run their Spark applications. And we support the latest developer tools and guidance, ensuring that you can develop and deploy your Spark applications with confidence and ease.Run your Spark applications individually or deploy them with ease on Databricks WorkflowsRun Spark notebooks with other task types for declarative data pipelines on fully managed compute resourcesWorkflow monitoring allows you to easily track the performance of your Spark applications over time and diagnosis problems within a few clicksBest price/performance for Spark workloadsRunning your Spark workloads on the Databricks Lakehouse Platform means you benefit from Photon – a fast C++, vectorized execution engine for Spark and SQL workloads that runs behind Spark’s existing programming interfaces. Photon provides record-breaking query performance at low cost while leveraging the latest in modern hardware architectures such as AWS Graviton.In addition to lightning-fast performance, Spark on Databricks achieves lower overall TCO through capabilities such as dynamic autoscaling, so you only pay for what you use. Databricks also offers GPU and spot instances.End-to-end analytics and unified governance with the Databricks Lakehouse PlatformWhile other platforms require you to integrate multiple tools and manage different governance models, Databricks unifies data warehouse, data lake and data streaming in one simple Lakehouse Platform to handle all your data engineering, analytics and AI use cases end-to-end. It’s built on an open and reliable data foundation that efficiently handles all data types, unifies batch and streaming, and applies one common security and governance model across all your data and cloud platforms.Continued innovationThe 2022 SIGMOD Systems Award recognized Spark as an innovative, widely used, open source, unified data processing system encompassing relational, streaming and machine learning workloads.And the innovation continues. Recently we introduced Spark Connect and Project Lightspeed.Spark Connect decouples the client and server for better stability and allows for Spark applications everywhere.Project Lightspeed, the next generation of Spark Structured Streaming, further delivers on predictable low latency and enhanced functionality for processing events.Ready to get started?Try Spark on Databricks todayProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/avinash-sooriyarachchi

Avinash Sooriyarachchi - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAvinash SooriyarachchiSenior Solutions Architect at DatabricksBack to speakersAvinash Sooriyarachchi is a Solutions Architect at Databricks. His current work involves working with large Retail and Consumer Packaged Goods organizations across the United States and enabling them to build Machine Learning based systems. His specific interests include streaming machine learning systems and building applications leveraging foundation models. Avi holds a Master’s degree in Mechanical Engineering and Applied Mechanics from the University of Pennsylvania.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/blog/2022/06/28/introducing-databricks-marketplace-an-open-marketplace-for-all-data-and-ai-assets.html

Introducing Databricks Marketplace, an Open Marketplace for Data Solutions - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks MarketplaceAn open marketplace for data solutionsby Matei Zaharia, Zaheera Valani, Jay Bhankharia, Sachin Thakur, Itai Weiss and Steve MahoneyJune 28, 2022 in AnnouncementsShare this postWe're pleased to announce Databricks Marketplace, an open marketplace for exchanging data products such as datasets, notebooks, dashboards, and machine learning models. To accelerate insights, data consumers can discover, evaluate, and access more data products from third-party vendors than ever before. Providers can now commercialize new offerings and shorten sales cycles by providing value-added services on top of their data. Databricks Marketplace is powered by Delta Sharing allowing consumers to access data products without having to be on the Databricks platform. This open approach allows data providers to broaden their addressable market without forcing consumers into vendor lock-in. Databricks MarketplaceThis blog will discuss the key limitations of the existing data marketplaces and our vision for an open marketplace on the Databricks Lakehouse platform Existing data marketplaces fail to maximize business value for data providers and data consumersThe demand for 3rd party data to make data-driven innovations is greater than ever and data marketplaces act as a bridge between data providers and data consumers to help facilitate the discovery and delivery of datasets. However, as organizations continue leveraging more third party data, the value these platforms provide has not kept up with the needs of both providers and consumers. Challenges for data consumersData consumers value ease of data discovery and frictionless data evaluation from a data marketplace. However, existing data marketplaces that provide only datasets miss out on one of the key considerations for data consumers which is the context around the data. In most of the current data marketplaces, consumers receive a brief overview of the datasets, and maybe a few sample queries. This often leads to frustration as consumers have to spend time understanding the data model and going back and forth with the data provider's support teams before they are able to determine if it is the right fit for their analytic needs. Additionally, most current marketplaces work in walled garden environments. Data exchange can only be done on their closed platforms and sometimes only within their proprietary data formats. There are limited options to access the data from 3rd party tools or platforms seamlessly and the data consumers are forced to be on the platform, creating lock-in. Challenges for data providersFrom the data providers' perspectives, two important measures of success are an increase in sales and a lowering in operational cost. However, most data marketplaces fall short on both of these measures. With existing data marketplaces, data providers can only package and distribute datasets. And most marketplaces limit providers to only offering a brief write-up or out-of-context query examples to augment their dataset product profiles. Data consumers end up incurring significant effort and downstream costs to evaluate these datasets. This results in cumbersome onboarding, unnecessary long sales cycles, and eventually lost revenue opportunities. Additionally, many data marketplaces require data providers to load data into their proprietary format, leverage their compute, and replicate data into different clouds and regions in which their customers operate. This quickly increases compute costs and operational burden as more and more moving parts are added to the system to maintain parity across cloud providers/regions. As the number of datasets and their volume grows, data providers must consider these costs and trade-off decisions. Some data providers may be left with the decision to deprioritize potentially valuable datasets as the cost to commercialize them grows. Unlock business value with Databricks MarketplaceThe vision behind Databricks Marketplace is to address these problems and help. consumers and providers achieve their business objectives. Benefits for Data ConsumersFaster time to insightsWith the Databricks marketplace, Data consumers can get access not only to just datasets but other data assets including dashboards, notebooks, and ML models. This provides data consumers an easy way to evaluate data and accelerate time to insights. For example, data consumers can leverage a starter notebook to do exploratory data analysis or a machine learning model that helps predict future rankings of the dataset. Before requesting access to the data, Databricks hosted dashboards enable customers to explore the data live without any additional cost. All of this helps speed up the evaluation, acquisition, and analysis cycle and get more value from the data. An open marketplacePowered by Delta Sharing, Databricks Marketplace allows data consumers to seamlessly access the data products without the need to be on the Databricks platform. There is no lock-in, and it provides consumers options to maximize the data value from the tools of their choice. Benefits for Data ProvidersDistribute and monetize a wide array of data productsWith the Databricks Marketplace, providers can market and distribute not only just datasets, but also their other data products such as notebooks, dashboards, and models that are essential to help consumers realize the full value of a dataset. Lets say a provider is selling Environmental Social and Governance (ESG) data. The provider can package a notebook along with the data to show how the data can be utilized for NLP analysis, a dashboard that provides a visualization of the worst polluting companies, and a model that will show how the shared ESG data can provide recommendations on when a company's ESG ranking will change. With the existing data marketplaces, there is no easy way for providers to share all these highly valuable assets. Broaden the reach of the data productsWith Databricks Marketplace,data providers can expand their addressable market beyond the consumers who are on the Databricks Platform. This helps data providers increase the revenue potential of their data products. No replication of data productsDatabricks Marketplace allows data providers to share their data products without having to move or replicate the data products from their cloud storage. This allows providers to deliver data products to other clouds, tools, and platforms from a single source. Providers may choose to replicate data products as desired, but they have the option to choose versus being forced to do so and incurring additional costs. What Databricks Partners are saying:"Databricks Marketplace is a compelling platform for us. We like the fact that it is open and provides us a way to reach existing and new types of personas for our data offerings. We see the platform as a key enabler to accelerate value with our data offerings to our customers"- Chris Anderson, CTO Intellectual Property Solutions, LexisNexis"Customers need solutions, not only raw data. Being able to package raw data along with the code and analytics on top of it is how we see customers consuming raw data in the future" - Ross Epstein, VP New Projects, Safegraph"Facteus is extremely excited to be part of the inception of the Databricks Marketplace. A marketplace built on their Delta Share protocol is a huge step forward in democratizing and simplifying data access." - Jonathan Chin, Co-Founder Head of Data and Growth, Facteus"With more than 1.2B non-identified patient records, IQVIA has unparalleled healthcare data and is focused on advancing innovation for a healthier world. We are looking forward to the upcoming launch of Databricks' Delta Sharing Marketplace to enable seamless data sharing with our customers, which will accelerate time to insights and value across the ecosystem." - Avinob Roy, VP & GM Product Management, IQVIASIGN UP TO BE A DATA PROVIDERTry Databricks for freeGet StartedRelated postsNow Generally Available: Introducing Databricks Partner Connect to Discover and Connect Popular Data and AI Tools to the LakehouseNovember 18, 2021 by Hiral Jasani and Himanshu Raja in Platform Blog Databricks is thrilled to announce Partner Connect, a one-stop portal for customers to quickly discover a broad set of validated data, analytics, and... Build Your Business on Databricks With Partner ConnectNovember 18, 2021 by Dave Eyler, Pankaj Dugar and Zaheera Valani in Platform Blog At Databricks we believe that to create the ultimate customer experience, we must leverage the work of more than just our employees and... Databricks’ 2022 Global Partner AwardsJune 27, 2022 by Kori O'Brien and Roger Murff in Company Blog Databricks has a partner ecosystem with over 600 partners globally that are critical to building and delivering the best data and AI solutions... See all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/blog/2021/03/23/introducing-databricks-on-google-cloud-now-in-public-preview.html

Introducing Databricks on Google Cloud - Now in Public Preview - The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorIntroducing Databricks on Google Cloud - Now in Public Previewby Hiral JasaniMarch 23, 2021 in AnnouncementsShare this postLast month, we announced Databricks on Google Cloud, a jointly-developed service that allows data teams (data engineering, data science, analytics, and ML professionals) to store data in a simple, open lakehouse platform for all data, AI and analytics workloads. Today, we are launching the public preview of Databricks on Google Cloud. When speaking to our customers, one thing is clear: they want to build modern data architectures to drive real business impact, whether that’s by personalizing customer experiences with ML, improving in-product gaming experience or delivering life-saving medical supplies (just to name a few). But many find themselves bogged down with unmanageable amounts of data across data types – structured, unstructured, and semi-structured data – while simultaneously dealing with a variety of applications. For just the day-to-day work, data teams must stitch together various open source libraries and tools for further analytics. Multiple handoffs between data science, ML engineering and deployment teams slow down development. Complexity and cost of transferring data between multiple disparate data systems and challenges managing multiple copies of data and security models add to the overhead. With these pain points in mind, we believe the way to build a best-in-class Lakehouse platform is to build with open standards. Open standards, open APIs, open platform -- it gives customers the choice to build their modern data architecture based on services with a simple, collaborative experience. Google Cloud shares this “vision of openness” with an open cloud service, meaning our joint customers have the choice to choose the right set of tools to solve any problem. Open data lake with Delta Lake and Google Cloud StorageThe open technology that allows us to unify analytics and artificial intelligence (AI) with a lakehouse on top of your existing data lake is Delta Lake. Data lakes are an affordable way to store large amounts of raw data (structured, unstructured, video, text, audio), often in open source formats such as the widely-used Apache Parquet. Yet, many companies struggle to run their analytics and AI applications in production as they face many of the challenges listed below. Delta Lake is an open format storage layer that delivers reliability, performance and governance to solve these data lake challenges. Databricks on Google Cloud is based on Delta Lake and the Parquet format, so you can keep all your data in Google Cloud Storage (GCS) without having to move it or copy it in several places. This allows you to store and manage all your data for analytics on your data lake. Faster experimentation with easy-to-use ML & AI servicesOnce you have an open data lake, you have laid the foundation for your data science teams to develop and train their machine learning models. With the availability of Databricks on Google Cloud, data scientists and ML engineers can use our collaborative data science and managed MLflow capabilities with the data in Google Cloud Storage or BigQuery Storage. Databricks on Google Cloud is also integrated with Google Cloud’s suite of AI services. For example, you can deploy MLflow models to AI Platform Predictions for online serving or use AI Platform’s pre-trained ML APIs and AutoML for vision, video, translation and natural language processing. ConclusionDatabricks on Google Cloud brings a shared vision to combine the open platform with the open cloud for simplified data engineering, data science and data analytics. Want to learn more about how this joint solution unifies all your analytics and AI workloads? Register for our launch event with Databricks CEO & Co-founder Ali Ghodsi and Google Cloud CEO Thomas Kurian for a deep dive into the benefits of an open Lakehouse platform and how Databricks on Google Cloud drive data team collaboration. GET STARTED FOR FREETry Databricks for freeGet StartedSee all Announcements postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/chunxu-tang/#

Chunxu Tang - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingChunxu TangResearch Scientist at AlluxioBack to speakersDr. Chunxu Tang is a Research Scientist at Alluxio and a committer of PrestoDB. Prior to Alluxio, he served as a Senior Software Engineer in Twitter’s data platform team, where he gained extensive experience with a wide range of data systems, including Presto, Zeppelin, BigQuery, and Druid. He received his Ph.D. from Syracuse University, where he conducted research on distributed collaboration systems and machine learning applications.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/br/resources/whitepaper/mit-cio-vision-2025?itm_data=home-promocard2-mit-cio-vision-2025

Visão de CIOs para 2025: Preenchendo a lacuna entre BI e AI - DatabricksRelatórioVisão de CIOs para 2025Preenchendo a lacuna entre BI e AIPesquisa global de CIOs sobre adoção de IA orientada para o valor de negócioVeja como as principais empresas e organizações estão superando seus maiores desafios de dados para dominar a IA. No novo relatório de pesquisa do MIT Technology Review, você terá informações de 600 CIOs em 18 países e 14 setores.Como os CIOs priorizam a adoção da IA? Como eles estão investindo em melhorias em sua estratégia de dados?Obtenha respostas de entrevistas detalhadas com executivos C-level da Procter & Gamble, Johnson & Johnson, Cummins, Walgreens, S&P Global, Marks & Spencer e muito mais.Explore as principais descobertas sobre as perspectivas do CIO:72% dizem que os dados são o maior desafio para IA e 68% dizem que unificar sua plataforma de dados para analytics e IA é crucial94% dizem que já estão usando IA em LOBs e mais da metade espera que a IA seja difundida até 202572% acreditam que a multicloud é crítica e muitos oferecem suporte a padrões abertos para preservar a flexibilidade estratégicaBaixe o relatórioProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Aviso de privacidade|Termos de Uso|Suas opções de privacidade|Seus direitos de privacidade na Califórnia

https://www.databricks.com/dataaisummit/speaker/anindya-saha/#

Anindya Saha - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAnindya SahaML Platform Software Engineer at nullBack to speakersAnindya Saha is a Machine Learning Platform Engineer, focusing on enabling distributed computing solutions for machine learning and data engineering. He has led implementation of Spark on Kubernetes support on ml platform for feature engineering at scale. He also worked on enabling multi gpus multi nodes distributed model training on machine learning platform.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/david-skinner

David Skinner - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingDavid SkinnerChief Strategy Officer at AcxiomBack to speakersLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/glossary/dna-sequence

What is a DNA Sequence?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDNA SequenceAll>DNA SequenceTry Databricks for freeGet StartedWhat is a DNA Sequence?The DNA sequence is the process of determining the exact sequence of nucleotides of DNA (deoxyribonucleic acid).  Sequencing DNA the order of the four chemical building blocks - adenine, guanine, cytosine, and thymine also known as bases, occur within the DNA molecule. The first methods for sequencing DNA were developed in the middle 1970s by Fred Sanger, and by Walter Gilbert and Allan Maxam. The first DNA fragment that has been sequenced belonged to a  virus named T4 bacteriophage that specifically infects the Escherichia coli bacteria. Since the completion of the Human Genome Project, a number of new methods were being developed for large-scale sequencing. The technological improvements and automation have reached a point where labs can sequence well over 100,000 billion bases per year. A number of new methods have been developed for large-scale sequencing; these new methods can target large numbers of short DNA fragments or even entire chromosomes.DNA Sequencing MethodsThere are two main types of DNA sequencing: The Sanger method, also known as dideoxy, which is the classical chain termination method. This method is still being used for determining the sequences of relatively long stretches of DNA, at low volumes. However, if a large number of molecules has to be quickly sequenced it will not be the best choice mainly due to its high costs and laborious work.The High-Throughput Sequencing (HTS) method also known as the Next-Generation Sequencing (NGS) technique. NGS is characterized by improved accuracy and speed, but also reduced manpower and cost.The implementation of the High-Throughput Sequencing method has expanded the applications for genomics. DNA sequencing is now being used as an integral part of basic science, translational research, medical diagnostics, and forensics.  Additional ResourcesData Analytics and Machine Learning for the Life Sciences IndustryGenome Sequencing in a NutshellPractical Genomics with Apache SparkBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/atiyah-curmally/#

Atiyah Curmally - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingAtiyah CurmallyPrincipal Environmental Specialist at International Finance CorporationBack to speakersAtiyah Curmally's career centers on a passion for sustainable impact investing in emerging markets. At the International Finance Corporation, she focuses on providing insights, guidance, and practical solutions to investors, enabling them to assess risks and make decisions through the environmental, social, and governance (ESG) lens. Atiyah leads the ESG innovation and data science portfolio, including conception and development of an artificial intelligence (AI) solution called MALENA.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/solutions/accelerators/supply-chain-distribution-optimization

Supply Chain Distribution Optimization | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWSolution AcceleratorSupply Chain Distribution OptimizationPre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook Get startedOptimize transportation costs and improve distribution network performanceThe delivery of goods across a global distribution network is highly costly and logistically complex. Manufacturers can use data and AI to address these operational challenges to maintain competitiveness and profitability in the marketplace. With the Databricks Lakehouse for Manufacturing, organizations can:Use linear programming (LP) to optimize product distribution at scaleTrain models to predict supply and demand of productsLeverage Apache SparkTM to easily speed up model training on Pandas DataFramesDownload notebookResourceseBookRead nowVideoWatch nowBlogRead nowDeliver AI innovation faster with Solution Accelerators for popular industry use cases. See our full library of solutionsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit?itm_data=menu-learn-dais23

Data and AI Summit 2023 - DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGeneration AILarge Language Models (LLM) are taking AI mainstream. Join the premier event for the global data community to understand their potential and shape the future of your industry with data and AI. Register NowSan Francisco, Moscone CenterJune 26 - 29, 2023Featured SpeakersTop experts, researchers and open source contributors from Databricks and across the data and AI community will speak at Data + AI Summit. Whether you’re an engineering wizard, ML pro, SQL expert — or you want to learn how to build, train and deploy LLMs — you’ll be in good company. See all speakersDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleAdi PolakData & AI Technologist, lakeFSAli GhodsiCo-founder and CEO, DatabricksManu SharmaCEO, LabelboxMatei ZahariaOriginal Creator of Apache Spark™ and MLflow; Chief Technologist, DatabricksLin QiaoCo-creator of PyTorch, Co-founder and CEO, FireworksSai RavuruSenior Manager of Data Science & Analytics, Jet BlueEmad MostaqueCEO, Stability.AIHarrison ChaseCreator of LangChainSatya NadellaChairman and CEO, Microsoft, Live Virtual GuestZaheera ValaniSenior Director of Engineering, DatabricksHannes MühleisenCreator of DuckDBBrooke WenigMachine Learning Practice Lead, DatabricksJitendra MalikComputer Vision Pioneer, Former Head of Facebook AI ResearchRobin SutaraField CTO, DatabricksLior GavishCEO and Co-founder, Monte Carlo DataDawn SongProfessor of EECS, UC BerkeleyReynold XinCo-founder and Chief Architect, DatabricksDaniela RusDirector, MIT CSAIL; Professor of EECS, MITPercy LiangProfessor of Computer Science, StanfordNat FriedmanCreator of Copilot; Former CEO, GitHubMichael CarbinCo-founder, MosaicML; Professor of EECS, MITKasey UhlenhuthStaff Product Manager, DatabricksWassym BensaidSr. Vice President, Software Development, RivianEric SchmidtCo-Founder, Schmidt Futures; Former CEO and Chairman, GoogleWhy attend?Join thousands of data leaders, engineers, scientists and analysts to explore all things data, analytics and AI — and how these are unified on the lakehouse. Hear from the data teams who are transforming their industries. Learn how to build and apply LLMs to your business. Uplevel your skills with hands-on training and role-based certifications. Connect with data professionals from around the world and learn more about all Data + AI Summit has to offer. SessionsWith more than 250 sessions, Data + AI Summit has something for everyone. Choose from technical deep dives, hands-on training, lightning talks, industry sessions, and more. Explore sessionsTechnologyExplore the latest advances in leading open source projects and industry technologies like Apache Spark™, Delta Lake, MLflow, Dolly, PyTorch, dbt, Presto/Trino, DuckDB and much more. You’ll also get a first look at new products and features in the Databricks Lakehouse Platform. Browse catalogNetworkingConnect with thousands of data + AI community peers and grow your professional network in social meetups, on the expo floor, or at our event party. Learn moreChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at “birds of a feather” meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark™, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingTrusted by the data communityHear data practitioners from trusted companies all over the world See agendaDon’t miss this year’s event!Register nowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/company/contact?contactReason=Request%20a%20Demo

Contact Us - DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWContact usNeed assistance with training or support? See these additional resources.DocumentationRead technical documentation for Databricks on AWS, Azure or Google CloudDatabricks CommunityDiscuss, share and network with Databricks users and expertsTrainingMaster the Databricks Lakehouse Platform with instructor-led and self-paced training or become a certified developerSupportAlready a customer? Click here if you are encountering a technical or payment issueOur office locationsSee all our office locations globally and get in touchKnowledge baseFind quick answers to the most frequently asked questions about Databricks products and servicesProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/product/collaborative-notebooks?itm_data=product-link-collaborativeNotebooks

Databricks Notebooks | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks NotebooksCollaborative data science with familiar languages and toolsTry for freeSchedule a demoWork across engineering, data science and machine learning teams in one workspace. Use multiple languages, built-in data visualizations and automatic versioning, all within Notebooks.BenefitsWork togetherShare Notebooks and work with peers across teams in multiple languages (R, Python, SQL and Scala) and libraries of your choice. Real-time coauthoring, commenting and automated versioning simplify collaboration while providing control.Share insightsQuickly discover new insights with built-in interactive visualizations, or leverage libraries such as Matplotlib and ggplot. Export results and Notebooks in HTML or IPYNB format, or build and share dashboards that always stay up to date.Production at scaleSchedule Notebooks to automatically run machine learning and data pipelines at scale. Create multistage pipelines using Databricks Workflows. Set up alerts and quickly access audit logs for easy monitoring and troubleshooting.FeaturesData AccessQuickly access available data sets or connect to any data source, on-premises or in the cloud.DashboardsShare insights with your colleagues and customers, or let them run interactive queries with Spark-powered dashboards.Multi-language supportExplore data using interactive notebooks with support for multiple programming languages within the same notebook, including R, Python, Scala and SQL.Run Notebooks as JobsTurn notebooks or JARs into resilient production jobs with a click or an API call.Interactive VisualizationsVisualize insights through a wide assortment of point-and-click visualizations. Or use powerful scriptable options like Matplotlib, ggplot and D3.Jobs SchedulerExecute jobs for production pipelines on a specific schedule.Real-Time CoauthoringWork on the same notebook in real time while tracking changes with detailed revision history.Notebook WorkflowsCreate multistage pipelines with the control structures of the source programming language.CommentsLeave a comment and notify colleagues from within shared Notebooks.Notifications and LogsSet up alerts and quickly access audit logs for easy monitoring and troubleshooting.Automatic VersioningAutomatic change-tracking and versioning to help you pick up where you left off.Permissions ManagementQuickly manage access to each individual notebook, or a collection of Notebooks, and experiments, with one common security model.Git-based ReposSimplified Git-based collaboration, reproducibility and CI/CD workflows.ClustersQuickly attach Notebooks to auto-managed clusters to efficiently and cost-effectively scale up compute.Runs SidebarAutomatically log experiments, parameters and results from Notebooks directly to MLflow as runs, and quickly see and load previous runs and code versions from the sidebar.IntegrationsConnect to Tableau, Looker, Power BI, RStudio, Snowflake and also through your favorite IDEs such as VS Code — allowing data scientists and engineers to use their tools of choice.How it worksShared and interactive Notebooks, experiments and extended files support allow data scientist teams to organize, share and manage complex data science projects more effectively throughout the lifecycle. APIs and Job Scheduler allow data engineering teams to quickly automate complex pipelines, while business analysts can directly access results via interactive dashboards.Overview of collaborative featuresVisualize your dataManage, schedule, and scale nodesCustomersResourcesDocumentationNotebooksJobseBooks and WebinarsThe Big Book of Data Science Use CasesThe Big Book of Machine Learning Use CasesAutoML Rapid, simplified machine learning for everyoneMLOps Virtual Event: Standardizing MLOps at ScaleAutomating the ML Lifecycle With Databricks Machine LearningThe Data Scientist’s Guide to Apache Spark™The Apache Spark™ CollectionMLOps Virtual EventManaging the Complete Machine Learning LifecycleProduct DemoCollaboration in DatabricksVisualizations in DatabricksCase StudyHPNielsenReady to get started?Try Databricks for freeProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/company/founders

Founders | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLeadershipWith a long-term vision, our leadership team leverages decades of experience to chart a new course for data and AIMeet our teamExecutive teamFoundersBoard of directorsAli GhodsiCo-founder and Chief Executive OfficerIon StoicaCo–founder and Executive ChairmanMatei ZahariaCo–founder and Chief TechnologistPatrick WendellCo–founder and VP of EngineeringReynold XinCo–founder and Chief ArchitectAndy KonwinskiCo–founder and VP of Product ManagementArsalan Tavakoli-ShirajiCo-founder and SVP of Field EngineeringProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

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Databricks Machine Learning | DatabricksSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT さようなら、データウェアハウス。こんにちは、レイクハウス。 データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。 今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)   製造業のためのレイクハウスを発見する コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日 直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOW機械学習データを活用する機械学習で AI プロジェクトを加速無料トライアルデモをリクエスト Helly Dolly :オープンな大規模言語モデル(LLM) を自身でトレーニング 2023年5月18日（木）午後4時00分 (JST) ご登録Databricks プラットフォームで機械学習を展開マネージド MLflowモデルレジストリML ランタイムコラボレーション型 Notebook特徴量ストア（Feature Store）AutoML説明可能なAIリポジトリモデル監視モデルの提供オープンなレイクハウスアーキテクチャを基盤とする Databricks のプラットフォームは、機械学習のためのデータの準備や処理を効率化し、チーム間のコラボレーションを支援し、実験から本番までの機械学習ライフサイクルの合理化を可能にします。6百万ドル以上の節約CONA Servicesは、何十万もの店舗のサプライチェーンを最適化するために、MLライフサイクルの全てにDatabricksを使用しています。詳しく見る3.9百万レアルの節約Viaは、機械学習を活用して正確な需要予測を行い、計算コストを25%削減しました。詳しく見る5,000万ドル以上のコスト削減アムジェン、データサイエンス連携を改善し、創薬の加速と運用コストの削減を実現。詳しく見る機械学習データをシンプルにDatabricks ML は、オープンなレイクハウスアーキテクチャを基盤として構築されており、Delta Lake が組み込まれています。機械学習チームによる、あらゆる規模、種類のデータのアクセス、探索、準備を可能にします。データエンジニアリングのサポートなしで、特徴量をセルフサービスで本稼働パイプラインに組み込めます。実験追跡とガバナンスの自動化マネージド MLflow により、実験を自動的に追跡し、トレーニング実行ごとのパラメータ、メトリクス、データとコードのバージョン、モデルの成果物を記録できます。実行履歴をすぐに確認でき、結果を比較したり、必要に応じて過去の結果を再現したりすることも可能です。本番環境に最適なモデルのバージョンを特定した後は、モデルレジストリに登録し、展開ライフサイクル全体のハンドオフを簡素化できます。モデルのライフサイクル全体を動的に管理トレーニングされたモデルを登録すると、モデルレジストリを使用してモデルのライフサイクルを共同管理できます。モデルのバージョン管理や移動は、実験、ステージング、本番環境、アーカイブなどさまざまな段階で可能です。ライフサイクル管理は、ロールベースのアクセス制御に従って、承認やガバナンスのワークフローと統合されています。また、コメントやメールの通知機能により、データチームのコラボレーション環境が充実します。ML モデルの大規模展開を低レイテンシでサーバーの管理やスケールの制限を気にすることなく、ワンクリックでモデルをデプロイできます。Databricks を使用することで、エンタープライズレベルの高可用性で、モデルを REST API エンドポイントとして任意の場所にデプロイできます。製品コンポーネントコラボレーション型 NotebookDatabricks の Notebook は、Python、R、SQL をネイティブにサポートしており、ユーザーは任意の言語やライブラリを使用できます。気づきの視覚化と共有も容易です。詳しく見る機械学習のランタイム最も一般的な ML フレームワーク（PyTorch、TensorFlow、scikit-learn など）のスケーラブルかつ信頼性のある分散処理により、事前に構成された ML 最適化クラスタにワンクリックでアクセスできます。このクラスタは、大規模に高性能を実現する最適化を備えています。詳しく見る特徴量ストア（Feature Store）自動的にログに記録されたデータソースを活用するデータリネージの検索機能で、特徴量の再利用を促進します。クライアントアプリケーションの変更を不要とするシンプルなモデル展開により、トレーニングやサービスに特徴量を活用できます。詳しく見るAutoMLAutoML は、グラスボックス的なアプローチによって、機械学習の専門家だけでなく市民データサイエンティストも支援します。すぐに使える高性能なモデルの提供はもとより、専門家による改良が可能なコードの生成もできます。詳しく見るマネージド MLflowマネージド MLflow は、MLライフサイクルにおいて世界をリードするオープンソースプラットフォームの MLflow 上に構築されています。エンタープライズセキュリティ、信頼性、スケーラビリティで、 ML モデルの実験から本番への迅速な移行を支援します。詳しく見る本番グレードのモデルサービングサーバレスコンピューティングを活用するオプションを備え、あらゆるスケールのモデルをワンクリックで容易に提供します。詳しく見るモデル監視モデルのパフォーマンスとそれがビジネス指標に与える影響をリアルタイムで監視します。Databricks は、ソースデータシステムでの修正が必要なモデルに対してもエンドツーエンドの可視性とリネージを提供します。ML ライフサイクル全体にわたるモデルとデータの品質を分析し、問題が発生する前にリスクを特定するのに役立ちます。詳しく見るリポジトリRepos は、Databricks での Git ワークフローを効率化し、自動化された CI/CD ワークフローとコードのポータビリティの活用を可能にします。詳しく見るデータブリックスソリューションへの移行Hadoop やエンタープライズ DWH などのレガシーシステムに関連するデータサイロ、パフォーマンス低下、高いコストにうんざりしていませんか？Databricks レイクハウスに移行することで、あらゆるデータ、分析、AI のユースケースに対応する最新のプラットフォームが実現します。データブリックスソリューションへの移行関連リソース 関連リソース一覧 データサイエンスや機械学習に関する eBook やビデオを探すには、リソースライブラリをご覧ください。 詳しく見るeBookMLOps のビッグブック新しい Delta Sharing ソリューションの詳細移行ガイド：Hadoop から Databricks への移行デモとブログデモ：Databricks の機械学習ソリューションHadoop からレイクハウスへの移行：成功のための 5 つのステップオンラインイベントAutoML：迅速でシンプルな機械学習MLOps オンラインイベント：大規模な MLOps の標準化Databricks のプラットフォームで機械学習のライフサイクルを自動化MLOps オンラインイベント：機械学習の大規模な運用機械学習プラットフォームの構築オンデマンド動画：Delta Lake ― レイクハウスの基盤Hadoop から Databricks への移行ガイド無料お試し・その他ご相談を承りますDatabricks 無料トライアル製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利

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Xiao Li - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingXiao LiSenior Engineering Manager at DatabricksBack to speakersXiao Li is a senior engineering manager, Apache Spark Committer and PMC member at Databricks. His main interests are on Spark and database engine. Previously, he was an IBM master inventor and an expert on asynchronous database replication and consistency verification. He received his Ph.D. from University of Florida in 2011.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

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Databricks Community Edition | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesDatabricks Community EditionCommunity Edition Terms of ServiceWelcome to Databricks Community Edition! We are pleased to provide Databricks Community Edition (the “Community Edition Services”) at no charge to those interested in learning and exploring the use of Databricks’ cloud-based data analytics platform, which enables data analysts and others to easily tap the power of Apache Spark and Databricks’ other proprietary functionality.  Your use of the Community Edition Services is governed by these Terms of Service, including the Arbitration Agreement (the “Terms”).  If you are using the Community Edition Services on behalf of an organization, you represent and warrant that you are authorized to bind that entity to these Terms, in which case “you” or “your” will refer to that entity (otherwise, such terms refer to you as an individual). If you do not have authority to bind your entity or do not agree with these Terms, you must not accept these Terms and may not use the Community Edition Services. 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THE FOREGOING LIMITATIONS AND EXCLUSIONS SHALL NOT APPLY WITH RESPECT TO ANY LIABILITY ARISING UNDER FRAUD, FRAUDULENT MISREPRESENTATION, GROSS NEGLIGENCE, OR ANY OTHER LIABILITY THAT CANNOT BE LIMITED OR EXCLUDED BY LAW. Some jurisdictions don’t allow the types of limitations in this paragraph, so they may not apply to you.  IN THESE JURISDICTIONS, EACH PARTY’S LIABILITY WILL BE FURTHER LIMITED TO THE GREATEST EXTENT PERMITTED BY LAW. You agree that this limitation of liability section is intended to allocate the risks between the parties, and that but for this limitation of liability, Databricks would not make available the Community Edition Services.Entire Agreement; No Third Party Rights. These Terms constitute the entire agreement between you and Databricks concerning the Community Edition Services and these Terms create no third party beneficiary rights.Termination, Modification, Waiver & Assignment.  Either of us may suspend or terminate your use of the Community Edition Services or delete Your Account or Your Content at any time and for any reason (including without limitation for any suspected violations of the Acceptable Use Policy); however, obligations of these Terms that by their nature should survive termination shall so survive.  In addition, we may revise these Terms from time to time, and will always post the most current version on our website.  If we elect to terminate your access to the Community Edition Services or delete Your Account or Your Content, or if a revision of these Terms meaningfully reduces your rights, we will make a reasonable attempt to notify you (by, for example, sending a message to the email address associated with your account or posting for a reasonable time period a message to the login page of the Community Edition Services) unless Databricks deems it necessary to suspend or terminate Your Account without notice.  By continuing to use or access the Community Edition Services after the revisions come into effect, you agree to be bound by the revised Terms. Databricks' failure to enforce a provision of these Terms is not a waiver of its right to do so later. If a provision of these Terms is found unenforceable, the remaining provisions of the Terms will remain in full effect and an enforceable term will be substituted reflecting our intent as closely as possible, provided that questions of unenforceability regarding the Arbitration Agreement shall be resolved according to the Severability Section of the Arbitration Agreement.  You may not assign or transfer any of your rights under these Terms, and any such attempt will be void. Databricks may assign these Terms and/or its rights under these Terms to any of its affiliates or to any successor in interest.DISPUTES; BINDING ARBITRATION AND CLASS ACTION WAIVERInformal Resolution. You agree with us that, if either of us has concerns, we must first work together to resolve any dispute informally without resorting to legal action.  You agree to contact us at [email protected] in the event you have a dispute prior to bringing a formal claim against Databricks.  If the dispute is not resolved within 30 calendar days from the notice date, either of us may bring a claim subject to the procedures set forth below. You and Databricks agree to the jurisdiction of the Northern District of California to resolve any dispute, claim, or controversy that relates to or arises in connection with these Terms (and any non-contractual disputes/claims relating to or arising in connection with them) and is not subject to mandatory arbitration as set forth below (the “Arbitration Agreement”).  Any disputes not subject to mandatory arbitration are subject to the laws of the state of California, without regard to choice or conflicts of law principles.Arbitration Agreement.  If you are located within the United States, you and Databricks agree that any dispute, claim, or controversy between you and Databricks arising in connection with or relating in any way to these Terms or to your relationship with Databricks as a user of the Community Edition Services (whether based in contract, tort, statute, fraud, misrepresentation, or any other legal theory, and whether the claims arise during or after the termination of these Terms) will be determined by mandatory binding individual (not class) arbitration. You and Databricks further agree that the arbitrator shall have the exclusive power to rule on his or her own jurisdiction, including any objections with respect to the existence, scope or validity of the Arbitration Agreement or to the arbitrability of any claim or counterclaim. The Arbitration Agreement will survive termination of the Terms.  You and Databricks agree that the Federal Arbitration Act applies and governs the interpretation and enforcement of the Arbitration Agreement (despite the choice of law provision above).Exceptions to Arbitration. Notwithstanding the prior clause, you and Databricks both agree that nothing in this Arbitration Agreement will be deemed to waive, preclude, or otherwise limit either of our rights, at any time, to (1) bring an individual action in a U.S. small claims court or (2) bring an individual action seeking only temporary or preliminary individualized injunctive relief in a court of law, pending a final ruling from the arbitrator. In addition, this Arbitration Agreement doesn’t stop you or us from bringing issues to the attention of federal, state, or local agencies. Such agencies can, if the law allows, seek relief against us on your behalf (or vice versa).Prohibition of Class and Representative Actions and Non-Individualized Relief. You and Databricks agree that each of us may bring claims against the other only on an individual basis and not as a plaintiff or class member in any purported class or representative action or proceeding.  Unless both you and Databricks agree otherwise, the arbitrator(s) may not consolidate or join more than one person’s or party’s claims and may not otherwise preside over any form of a consolidated, representative or class proceeding.  Also, the arbitrator(s) may award relief (including monetary, injunctive and declaratory relief) only in favor of the individual party seeking relief and only to the extent necessary to provide relief necessitated by that party’s individual claim(s).  Any relief awarded cannot affect other Databricks customers.Arbitration Procedures. Arbitration is more informal than a lawsuit in court.  Arbitration uses a neutral arbitrator or arbitrators instead of a judge or jury, and court review of an arbitration award is very limited.  However, the arbitrator(s) can award the same damages and relief on an individual basis that a court can award to an individual. The arbitrator(s) also must follow the terms of these Terms as a court would.  The arbitration will be conducted by the American Arbitration Association (referred to as the "AAA") under its rules and procedures, including the AAA's Consumer Arbitration Rules (as applicable), unless you have accepted these Terms as a representative of a business entity, in which case AAA’s Commercial Arbitration Rules shall govern (as applicable), in each case as modified by this Arbitration Agreement.  The AAA's rules and forms to commence arbitration are available at www.adr.org. A party who intends to seek arbitration must first send the other party, if to Databricks, by certified mail, a completed Demand for Arbitration. You should send this notice to Databricks at: Databricks, Inc., Attn: Legal Department, Re: Demand for Arbitration, 160 Spear St., Ste. 1300, San Francisco, CA 94105 USA (with a copy to [email protected]).  Databricks will send any notice to you to the address we have on file associated with your Databricks account (which may solely be at your account email address); it is your responsibility to keep your address up to date. All information called for in the notice must be provided including a description of the nature and basis of the claims the party is asserting and the relief sought. The arbitration shall be held in the county in which you reside or at another mutually agreed location.  If the value of the relief sought is $10,000 or less, you or Databricks may elect to have the arbitration conducted by telephone or based solely on written submissions, which election shall be binding on you and Databricks subject to the discretion of the arbitrator(s) to require an in-person hearing, if the circumstances warrant. In cases where an in-person hearing is held, you and/or Databricks may attend by telephone, unless the arbitrator(s) require otherwise. Any settlement offer made by you or Databricks shall not be disclosed to the arbitrator(s). The arbitrator(s) will decide the substance of all claims in accordance with applicable law, including recognized principles of equity, and will honor all claims of privilege recognized by law.  The arbitrator(s) shall not be bound by rulings in prior arbitrations involving different Databricks customers, but is/are bound by rulings in prior arbitrations involving the same Databricks customer to the extent required by applicable law. The award of the arbitrator(s) shall be final and binding, and judgment on the award rendered by the arbitrator(s) may be entered in any court having jurisdiction thereof.Costs of Arbitration. Payment of all filing, administration, and arbitrator fees will be governed by the AAA's rules (either Consumer or Commercial, as applicable), unless otherwise stated in this Arbitration Agreement.  If the value of the relief sought by an individual is $10,000 or less, at your request, Databricks will pay all filing, administration, and arbitrator fees associated with the arbitration. Any request for payment of fees by Databricks should be submitted by mail to the AAA along with your Demand for Arbitration and Databricks will make arrangements to pay all necessary fees directly to the AAA.  If the value of the relief sought by an individual is more than $10,000 and you are able to demonstrate that the costs of accessing arbitration will be prohibitive as compared to the costs of accessing a court for purposes of pursuing litigation on an individual basis, Databricks will pay as much of the filing, administration, and arbitrator fees as the arbitrator(s) deem necessary to prevent the cost of accessing the arbitration from being prohibitive.  In the event the arbitrator(s) determine the claim(s) you assert in the arbitration to be frivolous, you agree to reimburse Databricks for all fees associated with the arbitration paid by Databricks on your behalf that you otherwise would be obligated to pay under the AAA's rules.Severability. With the exception of any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above, if a court decides that any part of this Arbitration Agreement is invalid or unenforceable, the other parts of this Arbitration Agreement shall still apply. If a court decides that any of the provisions in the Prohibition of Class and Representative Actions and Non-Individualized Relief section above is invalid or unenforceable because it would prevent the exercise of a non-waivable right to pursue public injunctive relief, then any dispute regarding the entitlement to such relief (and only that relief) must be severed from arbitration and may be litigated in court; in such case you irrevocably consent to the personal jurisdiction of the state and federal courts in the Northern District of California and such dispute shall be governed by the laws of the state of California, without regard to choice or conflicts of law principles. All other disputes subject to arbitration under the terms of the Arbitration Agreement shall be arbitrated under its terms.Amendments to Arbitration Agreement. Notwithstanding any provision in the Terms to the contrary, you and we agree that if we make any amendment to this Arbitration Agreement (other than an amendment to any notice address or website link provided herein) in the future, that amendment shall not apply to any claim that was filed in a legal proceeding against Databricks prior to the effective date of the amendment.  The amendment shall apply to all other disputes or claims governed by this Arbitration Agreement that have arisen or may arise between you and Databricks. We will notify you of amendments to this Arbitration Agreement by posting the amended terms on https://www.databricks.com/legal/ce-termsofuse at least 30 days before the effective date of the amendments and by providing notice through email where possible.  If you do not agree to these amended terms, you may close Your Account within the 30-day period and you will not be bound by the amended terms.Last Updated April 9, 2019ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/hari-shankar

Hari Shankar - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingHari ShankarSenior Director, R&D at VizioBack to speakersHari Shankar is the Senior Director of R&D, Data Engineering, for Vizio, the connected home and entertainment leader. At Vizio, Hari was responsible for leading their Databricks and lakehouse migration, as well as managing their AdTech platform strategy. Prior to Vizio, Hari worked at Samsung, NetApp, and Sun Microsystems in technical leadership roles.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/glossary/what-are-datasets

What are Datasets?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatasetsAll>DatasetsTry Databricks for freeGet StartedDatasets are a type-safe version of Spark's structured API for Java and Scala. This API is not available in Python and R, because those are dynamically typed languages, but it is a powerful tool for writing large applications in Scala and Java. Recall that DataFrames are a distributed collection of objects of type Row, which can hold various types of tabular data. The Dataset API allows users to assign a Java class to the records inside a DataFrame, and manipulate it as a collection of typed objects, similar to a Java ArrayList or Scala Seq. The APIs available on Datasets are type-safe, meaning that you cannot accidentally view the objects in a Dataset as being of another class than the class you put in initially. This makes Datasets especially attractive for writing large applications where multiple software engineers must interact through well-defined interfaces. The Dataset class is parametrized with the type of object contained inside: Dataset in Java and Dataset[T] in Scala. As of Spark 2.0, the types T supported are all classes following the JavaBean pattern in Java, and case classes in Scala. These types are restricted because Spark needs to be able to automatically analyze the type T and create an appropriate schema for the tabular data inside your Dataset. Additional ResourcesDatabricks Datasets DocumentationCOVID-19 Datasets Now Available on DatabricksBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/de/solutions/industries/manufacturing-industry-solutions

Lösungen für das verarbeitende Gewerbe – DatabricksSkip to main contentPlattformDie Lakehouse-Plattform von DatabricksDelta LakeData GovernanceData EngineeringDatenstreamingData-WarehousingGemeinsame DatennutzungMachine LearningData SciencePreiseMarketplaceOpen source techSecurity & Trust CenterWEBINAR 18. Mai / 8 Uhr PT Auf Wiedersehen, Data Warehouse. Hallo, Lakehouse. Nehmen Sie teil, um zu verstehen, wie ein Data Lakehouse in Ihren modernen Datenstapel passt. Melden Sie sich jetzt anLösungenLösungen nach BrancheFinanzdienstleistungenGesundheitswesen und BiowissenschaftenFertigungKommunikation, Medien und UnterhaltungÖffentlicher SektorEinzelhandelAlle Branchen anzeigenLösungen nach AnwendungsfallSolution AcceleratorsProfessionelle ServicesDigital-Native-UnternehmenMigration der Datenplattform9. Mai | 8 Uhr PT   Entdecken Sie das Lakehouse für die Fertigung Erfahren Sie, wie Corning wichtige Entscheidungen trifft, die manuelle Inspektionen minimieren, die Versandkosten senken und die Kundenzufriedenheit erhöhen.Registrieren Sie sich noch heuteLernenDokumentationWEITERBILDUNG & ZERTIFIZIERUNGDemosRessourcenOnline-CommunityUniversity AllianceVeranstaltungenData + AI SummitBlogLabsBaken26.–29. Juni 2023 Nehmen Sie persönlich teil oder schalten Sie für den Livestream der Keynote einJetzt registrierenKundenPartnerCloud-PartnerAWSAzureGoogle CloudPartner ConnectTechnologie- und DatenpartnerTechnologiepartnerprogrammDatenpartner-ProgrammBuilt on Databricks Partner ProgramConsulting- und SI-PartnerC&SI-PartnerprogrammLösungen von PartnernVernetzen Sie sich mit validierten Partnerlösungen mit nur wenigen Klicks.Mehr InformationenUnternehmenKarriere bei DatabricksUnser TeamVorstandUnternehmensblogPresseAktuelle Unternehmungen von DatabricksAuszeichnungen und AnerkennungenKontaktErfahren Sie, warum Gartner Databricks zum zweiten Mal in Folge als Leader benannt hatBericht abrufenDatabricks testenDemos ansehenKontaktLoginJUNE 26-29REGISTER NOWLakehouse für FertigungsunternehmenSenken Sie Kosten, steigern Sie die Produktivität und vereinheitlichen Sie Ihr Datenökosystem auf der einzigen Datenplattform, die speziell für die Verwendung von Daten in Fertigungsunternehmen entwickelt wurde.RegistrierenKontaktGeringere Gesamtbetriebskosten. Bessere Performance. Größere Skalierbarkeit.Lakehouse für FertigungsunternehmenWenn Sie Ihre Daten-, Analytics- und KI-Workloads mit integrierter Freigabe und Governance vereinheitlichen, können interne und externe Teams bei Bedarf auf die nötigen Daten zugreifen.Wirkung über die gesamte WertschöpfungsketteKundenbindungPräzise Ergebnisse und reibungslose Interaktionen für KundenMit einer 360-Grad-Sicht auf Kunden, Betrieb und Anlagen können Sie über den gesamten Produktlebenszyklus hinweg höchste Betriebszeit, Servicequalität und wirtschaftlichen Wert bieten und so die Personalisierung für Kunden, proaktiven Außendienst und differenzierte unternehmenskritische Lösungen fördern.BetriebseffizienzMitarbeiterproduktivitätProduktinnovationFertigungslösungen und PartnerKompromisslose Datenanalyse- und KI-Lösungen, die speziell für Fertigungsunternehmen entwickelt wurdenDatabricks Solution Accelerators sind speziell entwickelte Leitfäden – voll funktionsfähige Notebooks und Best Practices – für schnellere Ergebnisse in der Fertigungsbranche. Sparen Sie Zeit beim Entdecken, Entwerfen, Entwickeln und Testen in Anwendungsfällen wie digitalen Zwillingen, Gesamtanlageneffektivität, Prognosen und mehr.Monitoring der Gesamtanlageneffektivität und KPIsEine leistungsfähige und skalierbare End-to-End-Geräteüberwachung erzielen Erfassen und verarbeiten Sie schrittweise Daten von Sensor-/IoT-Geräten in einer Vielzahl von Formaten und berechnen Sie KPIs und Metriken, um wertvolle Erkenntnisse zu gewinnen.Erste SchrittePrognosen auf TeileebeneDen Bedarf auf Teileebene für eine optimierte Fertigung prognostizieren Prognostizieren Sie Ihren Bedarf auf Teileebene statt auf aggregierter Ebene, um Unterbrechungen in Ihrer Lieferkette zu minimieren und den Umsatz zu steigern.Erste SchritteDigitale ZwillingeDie betriebliche Effizienz steigern und die Entscheidungsfindung verbessern Verarbeiten Sie reale Daten in Echtzeit, beziehen Sie erkenntnisreiche Informationen durch umfassende Datenanalysen, liefern Sie sie an mehrere nachgelagerte Anwendungen und optimieren Sie den Anlagenbetrieb mit datengesteuerten Entscheidungen.Erste SchritteAccelerators für Fertigungsunternehmen erkundenWir sind eine Partnerschaft mit führenden Beratungsunternehmen eingegangen, um innovative, branchenspezifische Lösungen zu liefern. Databricks Brickbuilder Solutions helfen Ihnen, Kosten zu senken und den Wert Ihrer Daten zu steigern. Gestützt auf jahrzehntelange Branchenkenntnis – und entwickelt für die Databricks Lakehouse-Plattform – sind die Brickbuilder Solutions genau auf Ihre Bedürfnisse zugeschnitten.Intelligente Fertigung Nutzen Sie Ihre Daten, fördern Sie die Interoperabilität und stellen Sie mithilfe von Analysen und KI umfassende Informationen in großem Maßstab bereit.Mehr InformationenQualitätsprüfungenAutomatisieren Sie Ihre Qualitätskontrolle mit Computer Vision, um Defekte, Fremdkörper, Anomalien oder falsche Einstellungen zu erkennen.Mehr InformationenVorausschauendes Management von LieferrisikenVerbessern Sie die Sichtbarkeit der n-ten Ebene in Auftragsabläufen und bei der Lieferantenperformance, um die Effizienz zu steigern, Ausnahmen zu verwalten und die Ausfallsicherheit zu verbessern.Mehr InformationenAlle Partnerlösungen anzeigen„Databricks Lakehouse versetzt uns in die Lage, die Eintrittsbarriere für den Datenzugriff in unserem gesamten Unternehmen zu senken, damit wir die innovativsten und zuverlässigsten Elektrofahrzeuge der Welt bauen können.“ – Wassym Bensaid, Vice President of Software Development, Rivian „Die Verwendung von Databricks hat sich im Laufe der Jahre erheblich ausgeweitet. Anfangs haben wir Databricks als Big Data- und KI-Plattform genutzt, aber der Anwendungsbereich hat sich ausgeweitet. Wir haben eine völlig andere Klasse von Citizen Engineers und Data Scientists, die Databricks als modernes Business-Intelligence-Tool verwenden, um intelligentere Geschäftsentscheidungen zu treffen.“ – Daniel Jeavons, General Manager, Advanced Analytics CoE, Shell „Die Databricks-Plattform hat uns geholfen, Risiken für die Triebwerksverfügbarkeit zu minimieren, Vorlaufzeiten für Ersatzteile zu verkürzen und die Lagerumschlagszeiten effizienter zu gestalten – all dies ermöglicht es uns, TotalCare, das führende PBH-Wartungsprogramm (Power-by-the-Hour) der Luftfahrtbranche, bereitzustellen.“ – Stuart Hughes, Chief Information and Digital Officer, Rolls-Royce Civil Aerospace RessourcenE-BookERP-Daten nutzbringend einsetzenWebinareVerbesserung der vorausschauenden Wartung für Unternehmen des verarbeitenden Gewerbes mit Daten und KIE-BookVier Kräfte, die die intelligente Fertigung vorantreibenMöchten Sie loslegen?Wir würden uns freuen, Ihre Geschäftsziele zu verstehen und zu erfahren, wie unser Serviceteam Ihnen zum Erfolg verhelfen kann.DATABRICKS KOSTENLOS TESTENKontaktProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoProduktPlatform OverviewPreiseOpen Source TechDatabricks testenDemoLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLearn & SupportDokumentationGlossaryWEITERBILDUNG & ZERTIFIZIERUNGHelp CenterLegalOnline-CommunityLösungenBy IndustriesProfessionelle ServicesLösungenBy IndustriesProfessionelle ServicesUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktUnternehmenÜber unsKarriere bei DatabricksDiversität und InklusionUnternehmensblogKontaktWeitere Informationen unter „Karriere bei DatabricksWeltweitEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Datenschutzhinweis|Terms of Use|Ihre Datenschutzwahlen|Ihre kalifornischen Datenschutzrechte

https://www.databricks.com/dataaisummit/speaker/siddharth-bhai

Siddharth Bhai - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingSiddharth BhaiSr. Manager, Product Management at DatabricksBack to speakersSiddharth Bhai is a product management leader at Databricks, with 15+ years of experience, including long stints at Google and Microsoft. He has deep experience in identity, security, provisioning, and cloud computing. He has spoken at major industry conferences, including Hybrid Identity Protection, Directory Experts Conference, Microsoft TechEd, and Google Cloud Next. This summer, he’s interested in hearing about how teams in the real world are using Databricks. Come say hi if you see him!Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/legal/security-addendum

Security Addendum | DatabricksPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLegalTermsDatabricks Master Cloud Services AgreementAdvisory ServicesTraining ServicesUS Public Sector ServicesExternal User TermsWebsite Terms of UseCommunity Edition Terms of ServiceAcceptable Use PolicyPrivacyPrivacy NoticeCookie NoticeApplicant Privacy NoticeDatabricks SubprocessorsPrivacy FAQsDatabricks Data Processing AddendumAmendment to Data Processing AddendumSecurityDatabricks SecuritySecurity AddendumLegal Compliance and EthicsLegal Compliance & EthicsCode of ConductThird Party Code of ConductModern Slavery StatementFrance Pay Equity ReportSubscribe to UpdatesSecurity AddendumThis Security Addendum is incorporated into and made a part of the written agreement between Databricks, Inc. (“Databricks”) and Customer that references this Security Addendum (“Agreement”). Databricks maintains a comprehensive documented security program that is based on industry standard security frameworks including ISO 27001 and ISO 27018 (the “Security Program”). Pursuant to the Security Program, Databricks implements and maintains administrative, physical, and technical security measures to protect the Platform Services and Support Services and the security and confidentiality of Customer Content (including any Customer Personal Data that may be contained therein) (each as defined in the Agreement) under Databricks’ control that is processed by Databricks in its provisioning of the Platform Services or Support Services (the “Security Measures”). Databricks’ compliance with this Addendum shall be deemed to satisfy any more general measures included within any Agreement, including the Service Specific Terms. In accordance with its Security Program, Databricks will, when any Customer Content is under its control: (i) comply with the Security Measures identified below with respect to such Customer Content, and (ii) where relevant, keep documentation of such Security Measures. Databricks regularly tests and evaluates its Security Program, and may review and update this Security Addendum at any time without notice, provided that such updates are equivalent (or enhance) security and do not materially diminish the level of protection afforded to Customer Content by these Security Measures.Deployment ModelShared Responsibility. Databricks operates in a shared responsibility model, where both Databricks and the Customer maintain security responsibilities. This is covered in more detail in our Documentation.Architecture. Databricks is a hybrid platform-as-a-service offering. The components responsible for managing and controlling the Platform Services are referred to as the ‘Databricks Control Plane’ and are hosted within a Databricks Cloud Service Provider account. The compute resources that perform data processing operations are referred to as the “Data Plane”. For certain Cloud Service Providers, the Data Plane may either be deployed in the Customer’s Cloud Service Provider account (known as the ‘Customer Data Plane’) or, for Databricks Serverless Compute, in a Databricks-controlled Cloud Service Provider account (known as the ‘Databricks Data Plane’).  Data Plane shall refer to both Customer Data Plane and Databricks Data Plane unless otherwise specified.Compute Resources. Compute resources are created and coordinated by the Databricks Control Plane and deployed into the Data Plane. Compute resources are launched as new virtual machines that leverage the latest base image and Databricks source code and do not have data from previous machines. When compute resources terminate, the data on their local hard drives is overwritten by Databricks or by the Cloud Service Provider.Data Storage of Customer Content. Customer Data and Customer Results. Customer Control. Most Customer Data is stored within the Customer’s own Cloud Service Provider account at rest (e.g., within Customer’s AWS S3 bucket) or within other Systems under Customer’s control.  Customer may choose where this Customer Data resides (other than the DBFS root, which is deployed into a storage bucket within the applicable Cloud Service Provider in the region in which the Data Plane is deployed). Please see the Documentation for more details.Databricks Control.  Small amounts of Customer Data may be stored within the Databricks Control Plane, including Customer Results and metadata about Customer Data (e.g., contained within the metastore). Databricks offers Customers options regarding the storage of certain Customer Content within the Platform Services (e.g., the location of Customer Results created by the use of interactive notebooks). Please see the Documentation for more details.Customer Instructional Input. Customer Instructional Input is stored at rest within the Databricks Control Plane.Deployment Region. Customers may specify the region(s) where their Platform Services Workspaces are deployed. Customers can choose to deploy the Data Plane into any supported Databricks region. The Databricks Control Plane is deployed into the same region. Databricks will not, without Customers’ permission, move a Customer Workspace into a different region. See the Documentation for details specific to Customer’s Cloud Service Provider.Databricks’ Audits & Certifications. Databricks uses independent third-party auditors to assess the Databricks Security Program at least annually, as described in the following audits, regulatory standards, and certifications: SOC 2 Type II (report available under NDA)ISO 27001ISO 27018HIPAA (AWS, for HIPAA-compliant deployments)PCI DSS (AWS, for PCI-compliant deployments)Administrative ControlsGovernance. Databricks’ Chief Security Officer leads the Databricks’ Information Security Program and develops, reviews, and approves (together with other stakeholders, such as Legal, Human Resources, Finance, and Engineering) Databricks’ Security Policies (as defined below).Change Management. Databricks maintains a documented change management policy, reviewed annually, which includes but is not limited to, evaluating changes of or relating to systems authentication.ISMS; Policies and Procedures. Databricks has implemented a formal Information Security Management System (“ISMS”) in order to protect the confidentiality, integrity, authenticity, and availability of Databricks' data and information systems, and to ensure the effectiveness of security controls over data and information systems that support operations. The Databricks Security Program implemented under the ISMS includes a comprehensive set of privacy and security policies and procedures developed and maintained by the security, legal, privacy, and information security teams (“Security Policies”). The Security Policies are aligned with information security standards (such as ISO 27001) and cover topics including but not limited to: security controls when accessing Customer Workspaces; confidentiality of Customer Content; acceptable use of company technology, systems and data; processes for reporting security incidents; and privacy and security best practices. The Security Policies are reviewed and updated annually.Personnel Training. Personnel receive comprehensive training on the Security Policies upon hire and refresher trainings are given annually. Personnel are required to certify and agree to the Security Policies and personnel who violate the Security Policies are subject to disciplinary action, including warnings, suspension and up to (and including) termination.Personnel Screening and Evaluation. All personnel undergo background checks prior to onboarding (as permitted by local law), which may include, but are not limited to, criminal record checks, employment history verification, education verification, and global sanctions and enforcement checks. Databricks uses a third-party provider to conduct screenings, which vary by jurisdiction and comply with applicable local law. Personnel are required to sign confidentiality agreements.Monitoring & Logging. Databricks employs monitoring and logging technology to help detect and prevent unauthorized access attempts to its network and equipment.Access Review. Active users with access to the Platform Services are reviewed at least quarterly and are promptly removed upon termination of employment. As part of the personnel offboarding process, all accesses are revoked and data assets are securely wiped.Third Party Risk Management. Databricks assesses the security compliance of applicable third parties, including vendors and subprocessors, in order to measure and manage risk. This includes, but is not limited to, conducting a security risk assessment and due diligence prior to engagement and reviewing external audit reports from critical vendors at least annually. In addition, applicable vendors and subprocessors are required to sign a data processing agreement that includes compliance with applicable data protection laws, as well as confidentiality requirements.Physical and Environmental ControlsDatabricks Corporate Offices. Databricks has implemented administrative, physical, and technical safeguards for its corporate offices. These include, but are not limited to, the below: Visitors are required to sign in, acknowledge and accept an NDA, wear an identification badge, and be escorted by Databricks personnel while on premisesDatabricks personnel badge into the officesBadges are not shared or loaned to others without authorizationPhysical entry points to office premises are recorded by CCTV and have an access card verification system at every door, allowing only authorized employees to enter the office premisesEquipment and other Databricks-issued assets are inventoried and trackedOffice Wi-Fi networks are protected with encryption, wireless rogue detection, and Network Access ControlCloud Service Provider Data Centers. Databricks regularly reviews Cloud Service Provider audits conducted in compliance with ISO 27001, SOC 1, SOC 2, and PCI-DSS. Security controls include, but are not limited to the list below: Biometric facility access controlsVisitor facility access policies and procedures24-hour armed physical securityCCTV at ingress and egressIntrusion detectionBusiness continuity and disaster recovery plansSmoke detection sensors and fire suppression equipmentMechanisms to control temperature, humidity and water leaksPower redundancy with backup power supplySystems & Network SecurityPlatform Controls. Isolation. Databricks leverages multiple layers of network security controls, including network-level isolation, for separation between the Databricks Control Plane and Customer Data Plane, and between Workspaces within the Databricks Data Plane. See documentation on Serverless Compute for more details on the difference between Serverless Compute and non-Serverless Compute.Firewalls & Security Groups. Firewalls are implemented as network access control lists or security groups within the Cloud Service Provider's account. Databricks also configures local firewalls or security groups within the Customer Data Plane.Hardening.Databricks employs industry standards to harden images and operating systems under its control that are deployed within the Platform Services, including deploying baseline images with hardened security configuration such as disabled remote root login, isolation of user code, and images are regularly updated and refreshed.For Systems under Databricks control supporting the production data processing environment, Databricks tracks security configurations against industry standard baselines such as CIS and STIG.EncryptionEncryption of data-in-transit. Customer Content is encrypted using cryptographically secure protocols (TLS v.1.2 or higher) in transit between (1) Customer and the Databricks Control Plane and (2) the Databricks Control Plane and the Data Plane.  Additionally, depending on functionality provided by the Cloud Service Provider, Customers may optionally encrypt communications between clusters within the Data Plane (e.g., by utilizing appropriate AWS Nitro instances).Encryption of data-at-rest. Customer Content is encrypted using cryptographically secure protocols (AES-128 bit, or the equivalent or better) while at rest within the Databricks Control Plane.  Additionally, depending on functionality provided by the Cloud Service Provider, Customers may optionally encrypt at rest Customer Content within the Data Plane. See Documentation on ‘local disk encryption’ for more details.Review. Cryptographic standards are periodically reviewed and selected technologies and ciphers are updated in accordance with assessed risk and market acceptance of new standards.Customer Options; Responsibilities. Customers may choose to leverage additional encryption options for data in transit within the Customer Data Plane or Databricks Data Plane as described in the Documentation (e.g., Customer may utilize AWS Nitro EC2 instances within the Customer Data Plane to provide additional encryption in transit). Customer shall, based on the sensitivity of the Customer Content, configure the Platform Services and Customer Systems to encrypt Customer Content where appropriate (e.g., by enabling encryption at rest for data stored within AWS S3).Monitoring & LoggingIntrusion Detection Systems. Databricks leverages security capabilities provided natively by Cloud Service Providers for security detection.Audit Logs. Generation. Databricks generates audit logs from Customer’s use of the Platform Services. The logs are designed to store information about material events within the Platform Services.Delivery. Customer may, depending on the entitlement tier of the Platform Services, enable delivery of audit logs.  It is Customer’s responsibility to configure this option.Integrity.  Databricks stores audit logs in a manner designed to protect the audit logs from tampering.Retention. Databricks stores audit logs for at least one year.Penetration Testing. Databricks conducts third-party penetration tests at least annually, employs in-house offensive security personnel, and also maintains a public bug bounty program.Vulnerability Management & Remediation. Databricks regularly runs authenticated scans against representative hosts in the SDLC pipeline to identify vulnerabilities and emerging security threats that may impact the Data Plane and Databricks Control Plane. Databricks will use commercially reasonable efforts to address critical vulnerabilities within 14 days, high severity within 30 days, and medium severity within 60 days measured from, with respect to publicly declared third party vulnerabilities, the date of availability of a compatible, vendor-supplied patch, or for internal vulnerabilities, from the date such vulnerability is confirmed. Databricks leverages the National Vulnerability Database’s Common Vulnerability Scoring System (CVSS), or where applicable, the U.S.-Cert rating, combined with an internal analysis of contextual risk to determine criticality.Patching. Control Plane. Databricks deploys new code to the Databricks Control on an ongoing basis.Data Plane. New Data Plane virtual machines use the latest applicable source code and system images upon launch and do not require Databricks to patch live systems. Customers are encouraged to restart always-on clusters on a periodic basis to take advantage of security patches.Databricks Personnel Login to Customer Workspaces.  Databricks utilizes an internal technical and organizational control tool called ‘Genie’ that permits Databricks personnel to log in to a Customer Workspace to provide support to our Customers and permits limited Databricks engineering personnel to log in to certain Platform Services infrastructure.  Customer may optionally configure certain limitations on the ability for Databricks personnel to access Customer Workspaces. Please see Documentation on ‘Genie’ for more details, including on which Cloud Service Providers this is offered.Corporate Controls.Access ControlsAuthentication. Databricks personnel are authenticated through single sign-on (SSO), 802.1x (or similar) where applicable, and use a unique user ID and password combination and multi-factor authentication. Privileges are consistent with least privilege principles. Security Policies prohibits personnel from sharing or reusing credentials, passwords, IDs, or other authentication information. If your identity provider supports the SAML 2.0 protocol, you can use Databricks’ SSO to integrate with your identity provider.Role-Based Access Controls (RBACs). Only authorized roles are allowed to access systems processing customer and personal data. Databricks enforces RBACs (based on security groups and access control lists), and restricts access to Customer Content based on the principle of 'least privilege' and segregation of responsibilities and duties.Pseudonymization. Information stored in activity logs and databases are protected where appropriate using a unique randomized user identifier to mitigate risk of re-identification of data subjects.Workstation Controls: Databricks enforces certain security controls on its workstations used by personnel, including: Full-disk encryptionAnti-malware softwareAutomatic screen lock after 15 minutes of inactivitySecure VPNIncident Detection & ResponseDetection & Investigation. Databricks’ dedicated Detection engineering team deploys and develops intrusion detection monitoring across its computing resources, with alert notifications sent to the Security Incident Response Team (SIRT) for triage and response. The SIRT employs an incident response framework to manage and minimize the effects of unplanned security events.Security Incidents; Security Breaches. “Security Breach” means a breach of security leading to any accidental or unlawful destruction, loss, alteration, unauthorized disclosure of, or access to Customer Data under Databricks control. A “Security Incident” is any actual or attempted breach of security that does not rise to the level of a Security Breach. A Security Breach shall not include an unsuccessful attempt or activity that does not compromise the security of Customer Data, including (without limitation) pings and other broadcast attacks of firewalls or edge servers, port scans, unsuccessful log-on attempts, denial of service attacks, packet sniffing (or other unauthorized access to traffic data that does not result in access beyond headers) or similar incidents. Databricks maintains a record of known Security Incidents and Security Breaches that includes description, dates and times of relevant activities, and incident disposition. Suspected and confirmed Security Incidents are investigated by security, operations, or support personnel; and appropriate resolution steps are identified and documented. For any confirmed Security Incidents, Databricks will take appropriate, reasonable steps to minimize product and Customer damage or unauthorized disclosure. All incidents are logged in an incident tracking system that is subject to auditing on an annual basis.Communications & Cooperation. In accordance with applicable data protection laws, Databricks will notify Customer of a Security Breach for which that Customer is impacted without undue delay after becoming aware of the Security Breach, and take appropriate measures to address the Security Breach, including measures to mitigate any adverse effects resulting from the Security Breach.Backups, Business Continuity, and Disaster RecoveryBusiness Continuity and Disaster Recovery. Databricks Business Continuity (BC) and Disaster Recovery (DR) plans are reviewed and drills are conducted annually.Data Resiliency. Databricks performs backups for the Databricks Control Plane (including any Customer Instructional Input stored therein), generally managed by the Cloud Service Provider capabilities, for data resiliency purposes in the case of a critical systems failure. While Databricks backs up Customer notebooks that persist in the Databricks Control Plane as part of its systems resiliency, those backups are maintained only for emergency recovery purposes and are not available for Customers to use on request for recovery purposes.No Data Restoration. Due to the hybrid nature of the Databricks Platform, Databricks does not provide backup for Customer Content, and Databricks is unable to restore an individual Customer’s Instructional Input upon request. To assist Customers in backing up Customer Instructional Input, Databricks provides certain features within the Platform Services (like the ability to synchronize notebooks via a customer’s Github or Bitbucket account).Self-service Access. Databricks makes available certain features within the Platform Services that permit customers to access, export and delete certain Customer Content (e.g., notebooks) contained within the Databricks Control Plane. Please see the Documentation related to ‘manage workspace storage’.Customer Managed Backups. Customers retain ownership of their Customer Content and must manage their own backups, including to the extent applicable, enabling backup within the Systems in which the Customer Data is stored.Data Deletion. During Use. The Platform Services provide Customers with functionality that permit Customers to delete Customer Content under Databricks’ control.Upon Workspace Cancellation. Customer Content contained within a Customer Workspace is permanently deleted within thirty (30) days following cancellation of the Workspace.Secure Software Development Lifecycle (“SDLC”)Security Champions. Databricks Engineering and the security organization co-run a Security Champions program, in which senior engineers are trained and socialized as virtual members of the security team. Security Champions are available to all engineering staff for design or code review.Security Design Review. Feature designs are assessed by security personnel for their security impact to the Databricks Platform, for example, additions or modifications to access controls, data flows, and logging.Security Training. Engineers are required to take Secure SDLC training, including but not limited to, content provided by OWASP.Peer Code Review. All production code must be approved through a peer code review process.Change Control. Databricks’ controls are designed to securely manage assets, configurations, and changes throughout the SDLC.Code Scanning. Static and dynamic code scans are regularly run and reviewed.Penetration Testing. As part of the Security Design Review process, certain features are identified and subjected to penetration testing prior to release.Code Approval. Functional owners are required to approve code in their area of responsibility prior to the code being merged for production.Multi-Factor Authentication. Accessing the Databricks code repository requires Multi-Factor Authentication.Code Deployment. Production code is deployed via automated continuous integration / continuous deployment (CI/CD) pipeline processes.  The release management teams are separated from the engineering teams that build the product.Production Separation. Databricks separates production Platform Services Systems from testing and development Platform Services Systems.Last Revised September 25, 2021.ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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Databricks ソリューションアクセラレータ | Databricks ユースケースSkip to main contentプラットフォームデータブリックスのレイクハウスプラットフォームDelta Lakeデータガバナンスデータエンジニアリングデータストリーミングデータウェアハウスデータ共有機械学習データサイエンス料金Marketplaceオープンソーステクノロジーセキュリティ＆トラストセンターウェビナー 5 月 18 日午前 8 時 PT さようなら、データウェアハウス。こんにちは、レイクハウス。 データレイクハウスが最新のデータスタックにどのように適合するかを理解するために出席してください。 今すぐ登録ソリューション業種別のソリューション金融サービス医療・ライフサイエンス製造通信、メディア・エンターテイメント公共機関小売・消費財全ての業界を見るユースケース別ソリューションソリューションアクセラレータプロフェッショナルサービスデジタルネイティブビジネスデータプラットフォームの移行5月9日 |午前8時(太平洋標準時)   製造業のためのレイクハウスを発見する コーニングが、手作業による検査を最小限に抑え、輸送コストを削減し、顧客満足度を高める重要な意思決定をどのように行っているかをご覧ください。今すぐ登録学習ドキュメントトレーニング・認定デモ関連リソースオンラインコミュニティ大学との連携イベントDATA+AI サミットブログラボBeacons2023年6月26日～29日 直接参加するか、基調講演のライブストリームに参加してくださいご登録導入事例パートナークラウドパートナーAWSAzureGoogle CloudPartner Connect技術・データパートナー技術パートナープログラムデータパートナープログラムBuilt on Databricks Partner ProgramSI コンサルティングパートナーC&SI パートナーパートナーソリューションDatabricks 認定のパートナーソリューションをご利用いただけます。詳しく見る会社情報採用情報経営陣取締役会Databricks ブログニュースルームDatabricks Ventures受賞歴と業界評価ご相談・お問い合わせDatabricks は、ガートナーのマジック・クアドラントで 2 年連続でリーダーに位置付けられています。レポートをダウンロードDatabricks 無料トライアルデモを見るご相談・お問い合わせログインJUNE 26-29REGISTER NOW業界向け Databricks業界に特化した効果的なデータ分析・AI ソリューション無料トライアルデモをリクエスト業界向けレイクハウス一覧通信、メディア・エンターテイメント視聴者満足度を高め、創造性を強化する詳しく見る金融サービス信頼性を信用性を高める詳しく見る医療・ライフサイエンス効果的なケアの発見と提供詳しく見る小売・消費財カスタマージャーニーで顧客に寄り添いブランド力を高める詳しく見る業界別searchHide filtersIndustry🤔No results available. Try adjusting the filters or start a new search.reset the list業種別ソリューション発案から PoC までを 2 週間で完了Databricks ソリューションアクセラレータは、成果創出を加速するフル機能の Notebook やベストプラクティスを含む目的に沿ったガイドです。ソリューションアクセラレータを使用することで、発見、設計、開発、テストにかかる時間を短縮でき、多くのお客様は、発案から PoC までをわずか 2 週間で完了させています。ソリューションアクセラレータを見るさっそく試してみませんか？まずは無料トライアルで Databricks のソリューションをお試しください無料トライアル製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ製品プラットフォーム料金オープンソーステクノロジーDatabricks 無料トライアルデモ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティ学習・サポートドキュメント用語集トレーニング・認定ヘルプセンター法務オンラインコミュニティソリューション業種別プロフェッショナルサービスソリューション業種別プロフェッショナルサービス会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ会社情報会社概要採用情報ダイバーシティ＆インクルージョンDatabricks ブログご相談・お問い合わせ採用情報言語地域English (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.プライバシー通知|利用規約|プライバシー設定|カリフォルニア州のプライバシー権利

https://www.databricks.com/blog/category/platform/solutions

The Databricks BlogSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWLoading...ProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/lewis-mbae

Lewis Mbae - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingLewis MbaeHead of Customer Engineering at RudderStackBack to speakersLewis leads Customer Engineering at RudderStack. His team's core focus is to be the trusted technical advisor for all RudderStack customers throughout their journey on the platform. Prior to RudderStack he spent 7 years at Fastly where he held senior roles in Sales Engineering. On the personal side, he grew up in Kenya and moved to the United States to attend college. He has a MS in Computer Science from Columbia as well as a BS in Electrical Engineering from StanfordLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/jim-hibbard

Jim Hibbard - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingJim HibbardSenior Developer Advocate at DatabricksBack to speakersJim Hibbard is a Developer Advocate at Databricks. Prior to that, he worked at Seattle Children’s Hospital where he developed frameworks and methods for integrating medical records with multi-omics datasets to improve care. He is currently working on improving machine learning infrastructure and model management as part of the extended MLflow team.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/blog/2019/11/21/a-day-at-the-2019-women-in-product-conference.html

A Day at the 2019 Women in Product ConferenceSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWCategoriesAll blog postsCompanyCultureCustomersEventsNewsPlatformAnnouncementsPartnersProductSolutionsSecurity and TrustEngineeringData Science and MLOpen SourceSolutions AcceleratorsData EngineeringTutorialsData StreamingData WarehousingData StrategyBest PracticesData LeaderInsightsIndustriesFinancial ServicesHealth and Life SciencesMedia and EntertainmentRetailManufacturingPublic SectorA Day at the 2019 Women in Product Conferenceby Anna Shrestinian, Allie Emrich, Julia Han and Rebecca LiNovember 21, 2019 in Company BlogShare this postFrom left to right: Shveta, Julia, Yardley Pohl (a WIP board member and co-founder), Anna, Allie, Cyrielle, and Rani at the Databricks boothDatabricks was a proud sponsor of the 2019 Women In Product conference which focuses on empowering women in product management and advocating for equal representation. We had a booth and happy hour where attendees could network with our product team, and learn more about our open roles. Read more about what this experience meant to the team members that attended below! What led you to your current position at Databricks?Anna Shrestinian, Senior Product Manager I am a product manager on identity and data security at Databricks. I work to solve our customers’ challenges with securing data at an enterprise scale. Rebecca Li, Staff Product Manager, Pricing and Portfolio I am a product manager on pricing, cost management, and usage visibility. I work to design a packaging & pricing model that drives Databricks’ adoption in the market; and optimizes the long-term revenue of the company. At the same time, I work to make sure customers have the right tools to closely monitor their usage and cost. Allie Emrich, Senior Program Manager, Product I’m a program manager on the product team who’s in charge of coordinating and communicating much of our roadmap and the updates that occur throughout the quarter. Program management is a funny position because it doesn’t necessarily have a conventional path. I started out working on the customer success side, and really enjoyed cross-departmental projects focusing on product launches. When I saw the role at Databricks that leveraged my skill set on the CS side, but allowed me to grow operationally on the product side, I knew it was an opportunity I couldn’t pass up. Cyrielle Simeone, Senior Product Marketing Manager, Data Science and Machine Learning I'm a product marketing manager for data science and machine learning at Databricks. My role primarily consists of developing deep domain and audience understanding, product messaging collateral, as well as go-to-market strategies and campaigns. It's funny, I didn’t originally plan on becoming a PMM, but I’m so glad I did. I graduated from a French generalist engineering school in 2006 with a specialization in image and signal processing. While curious and fascinated by math and science, I realized early on in my career that I was more interested in enabling people with technology and learning how they solved problems rather than becoming a specialist myself. The PMM role at Databricks is perfect for me in the sense that it sits at the intersection of product, customers, and sales, and gives me the opportunity to collaborate with extremely talented people across functions to bring to market ML products with a fantastic community fit, like MLflow. It allows me to stay abreast of practitioner needs and challenges, industry trends, and use cases across industries. It is a very diverse and demanding role, that can be very rewarding when executed well. Julia Han, Engineering Program Manager I’m an engineering program manager on the technical program management team. The technical program management team works on ensuring that there is alignment between the engineering and product management orgs. I work on reducing engineering overhead for project management and ensuring that proper coordination and communication is in place to facilitate execution for the engineering teams. Keynote Session with Diane von Furstenberg at the conferenceWhat did sponsoring the Women in Product conference mean to you?Anna Shrestinian, Senior Product Manager The energy at the Women in Product conference was invigorating. It was amazing to be surrounded by leaders in the field and hear their insights on Product skills as well as their inspiring stories. I am proud to see Databricks’ name alongside best-in-class organizations as a Gold Sponsor. It shows me our commitment to diversity and inclusion. Rebecca Li, Staff Product Manager, Pricing and Portfolio I was pleasantly surprised by the diversity of industries, experiences, and career trajectories of our guest speakers. Each of them shed light on a different area of expertise, and shared their unique story of how they became who they are today. It was very inspiring and encouraging to understand their mindset, their struggles and how they overcome them to build their unique character. The crowd was very energetic and engaging. You can tell the message resonates with the audience deeply, and it is a community of women in product that can help each other grow. It was a great experience and there needs to be more of them! Allie Emrich, Senior Program Manager, Product Many companies are focused on increasing gender diversity, but it’s great to be part of a company who is visibly taking action to help move the needle. The atmosphere at the conference was vivacious and contagious-full of attendees who were so excited to be there and connect with one another. Getting our name out there, and teaching people about what Databricks is all about was an experience for the books! Cyrielle Simeone, Senior Product Marketing Manager It was very exciting and humbling to be part of this initiative, and represent Databricks at the Women in Product conference. It demonstrates real commitment and initiatives towards more diversity and inclusion for us as we continue to scale, which is key. As a woman in tech, it was fantastic to get to meet and connect with the community, hear the experiences and aspirations of many women throughout the day, and introduce them to Databricks. The energy was vibrant and very communicative, I look forward to the next one! Julia Han, Engineering Program Manager As a woman in tech myself, it’s always eye opening to be able to hear and learn about the experiences of other women who are in tech. As Databricks scales, we want to see gender diversity make progress across the board by learning from other companies on their efforts and vice versa. It’s exciting to be part of a company that supports women who are seeking to connect and search for growth opportunities. We are so excited to be a part of a team that promotes growth and development and fosters us to learn from other subject matter experts in the field. Interested in working with our product teams here at Databricks? Check out our Careers Page!Learn More about Databricks Involvement with Women in Tech:https://www.databricks.com/sparkaisummit/north-america/women-in-uaTry Databricks for freeGet StartedSee all Company Blog postsProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/vicky-andonova/#

Vicky Andonova - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingVicky AndonovaManager, Applied Machine Learning at AnomaloBack to speakersVicky is a founding team member and the manager of the Applied Machine Learning team at Anomalo. Her team is responsible for building Anomalo’s machine-learning models and translating them into actionable insights for customers. Before Anomalo, Vicky worked at Instacart as a senior data scientist. There, she built Instacart’s experimentation platform and was the lead data scientist on a company initiative to improve grocery delivery quality. Vicky graduated with a BSEE from Columbia University.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/fr/company/contact

Nous contacter - DatabricksSkip to main contentPlateformeThe Databricks Lakehouse PlatformDelta LakeGouvernance des donnéesData EngineeringStreaming de donnéesEntreposage des donnéesPartage de donnéesMachine LearningData ScienceTarifsMarketplaceOpen source techCentre sécurité et confianceWEBINAIRE mai 18 / 8 AM PT Au revoir, entrepôt de données. Bonjour, Lakehouse. Assistez pour comprendre comment un data lakehouse s’intègre dans votre pile de données moderne. Inscrivez-vous maintenantSolutionsSolutions par secteurServices financiersSanté et sciences du vivantProduction industrielleCommunications, médias et divertissementSecteur publicVente au détailDécouvrez tous les secteurs d'activitéSolutions par cas d'utilisationSolution AcceleratorsServices professionnelsEntreprises digital-nativesMigration des plateformes de données9 mai | 8h PT   Découvrez le Lakehouse pour la fabrication Découvrez comment Corning prend des décisions critiques qui minimisent les inspections manuelles, réduisent les coûts d’expédition et augmentent la satisfaction des clients.Inscrivez-vous dès aujourd’huiApprendreDocumentationFORMATION ET CERTIFICATIONDémosRessourcesCommunauté en ligneUniversity AllianceÉvénementsSommet Data + IABlogLabosBeacons26-29 juin 2023 Assistez en personne ou connectez-vous pour le livestream du keynoteS'inscrireClientsPartenairesPartenaires cloudAWSAzureGoogle CloudContact partenairesPartenaires technologiques et de donnéesProgramme partenaires technologiquesProgramme Partenaire de donnéesBuilt on Databricks Partner ProgramPartenaires consulting et ISProgramme Partenaire C&SISolutions partenairesConnectez-vous en quelques clics à des solutions partenaires validées.En savoir plusEntrepriseOffres d'emploi chez DatabricksNotre équipeConseil d'administrationBlog de l'entreprisePresseDatabricks VenturesPrix et distinctionsNous contacterDécouvrez pourquoi Gartner a désigné Databricks comme leader pour la deuxième année consécutiveObtenir le rapportEssayer DatabricksRegarder les démosNous contacterLoginJUNE 26-29REGISTER NOWNous contacterAvez-vous besoin d'assistance ou d'aide vis-à-vis de la formation ? Veuillez consulter ces ressources supplémentaires.DocumentationLire la documentation technique pour Databricks sur AWS, Azure ou Google CloudCommunauté DatabricksDiscutez, partagez et interagissez avec les utilisateurs et les experts de DatabricksFormationDevenez un expert de la plateforme Lakehouse de Databricks grâce à des sessions dispensées par des formateurs ou que vous suivez à votre propre rythme. Ou devenez développeur certifié.AideDéjà client ? Cliquez ici si vous rencontrez un problème technique ou lié au paiementSites des bureauxDécouvrez tous nos bureaux dans le monde et contactez-nous.Base de connaissancesTrouvez des réponses rapides aux questions les plus fréquemment posées sur les produits et services de DatabricksProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoProduitPlatform OverviewTarifsOpen Source TechEssayer DatabricksDémoLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneLearn & SupportDocumentationGlossaryFORMATION ET CERTIFICATIONHelp CenterLegalCommunauté en ligneSolutionsBy IndustriesServices professionnelsSolutionsBy IndustriesServices professionnelsEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterEntrepriseNous connaîtreOffres d'emploi chez DatabricksDiversité et inclusionBlog de l'entrepriseNous contacterDécouvrez les offres d'emploi chez Databrickspays/régionsEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Avis de confidentialité|Conditions d'utilisation|Vos choix de confidentialité|Vos droits de confidentialité en Californie

https://www.databricks.com/dataaisummit/pricing/#

Pricing - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingPricingConference Full Conference PassThe full conference pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access. $1795 IN-PERSON Group DiscountGroups of 4 or more. Must be purchased in one transaction. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access. $1295 IN-PERSONEACH GOV/EDU/NFPDiscounted pass for Government/Education/Non Profit Organization employees. Pass includes keynotes, Expo Hall, breakout sessions, networking events and on-demand access. $1395 IN-PERSON Virtual ExperienceThe free virtual experience includes livestreamed keynotes and unlimited access to on-demand sessions following the event. $0 VIRTUALTraining Two-Day CourseThis includes a two-day course and the certification exam. $1125 IN-PERSON Full-Day TrainingA comprehensive training workshop including a deep dive into your chosen topic. $750 IN-PERSON Half-Day TrainingA 4-hour, in-depth session covering your chosen topic. $375 IN-PERSONCertification Certification ExamRegister for training and take a certification exam onsite for free. $0 IN-PERSONChoose your experienceGet access to all the sessions, training, and special events live in San Francisco or join us virtually for the keynotes.RECOMMENDEDActivitiesIn Person EventVirtual EventKeynotesBreakout Sessions300+10Hands-on Training Courses for Data Engineering, Machine Learning, LLMs, and many onsite certificationsConnect with other data pros at “birds of a feather” meals, happy hours and special eventsLightning talks, AMAs and meetups on topics such as Apache Spark™, Delta Lake, MLflow and DollyAccess to 100+ leading data and AI companies in Dev Hub + ExpoIndustry Forums for Financial Services, Retail and Consumer Goods, Healthcare and Life Sciences, Communications, Media and Entertainment, Public Sector, and Manufacturing and EnergySee pricingDon’t miss this year’s event!Register NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/glossary/anomaly-detection

What is Anomaly Detection?PlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWAnomaly DetectionAll>Anomaly DetectionTry Databricks for freeGet StartedAnomaly Detection is the technique of identifying rare events or observations which can raise suspicions by being statistically different from the rest of the observations. Such “anomalous” behavior typically translates to some kind of a problem like credit card fraud, a failing machine, or a cyber attack. In finance, with thousands or millions of transactions to watch, anomaly detection can help point out where an error is occurring, enhancing root cause analysis and quickly getting support on the issue. Anomaly detection helps the monitoring cause of chaos engineering by detecting outliers and informing the responsible parties to act. Machine Learning and AI are increasingly being used for anomaly detection for fraud detection and Anti-Money Laundering (AML).Additional ResourcesSmarter risk and compliance with data and AIIdentify Fraud With Geospatial Analytics and AIHow to build: Rule-based AI models to combat financial fraudAnti-Money Laundering Solutions at Scale Using Databricks Lakehouse PlatformBack to GlossaryProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.Privacy Notice|Terms of Use|Your Privacy Choices|Your California Privacy Rights

https://www.databricks.com/dataaisummit/speaker/michael-sanky/#

Michael Sanky - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMichael SankyRVP, Industry Solutions, Healthcare and Life Sciences at DatabricksBack to speakersBusiness leader focusing on strategy, products, and business development in the intersection of science and IT. Helping Life Sciences companies accelerate and improve discovery by combining Technology and Human Ingenuity to enable Collaboration, Data Science, Digital Twins, AI, and Analytics in the Cloud.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/kr/try-databricks?itm_data=Homepage-HeroCTA-Trial

Databricks 무료로 체험하기 | DatabricksDatabricks 무료로 체험하기AWS, Microsoft Azure 또는 Google Cloud 중 원하는 클라우드 서비스에서 14일 동안 Databricks 플랫폼 전체를 무료로 체험해 보세요.데이터 수집 단순화 및 ETL 자동화가 가능합니다.수백 개의 소스에서 데이터를 수집해 보세요. 간단한 방식으로 데이터 파이프라인을 구축하실 수 있습니다.원하는 언어로 협업이 가능합니다.공동 저작, 자동 버전 관리, Git 통합, RBAC를 활용하여 Python, R, Scala 및 SQL로 코딩하세요.클라우드 데이터 웨어하우스보다 12배 더 우수한 가격 대비 성능전 세계 7,000개 고객사가 BI부터 AI에 이르는 모든 워크로드를 위해서 Databricks 를 선택한 이유를 알아보세요.Databricks 계정 생성하기1/2이름성회사 이메일회사직함전화번호(선택사항)보기 중에서 선택하세요국가계속개인 정보 보호 고지(업데이트됨)이용약관귀하의 개인 정보 선택귀하의 캘리포니아 프라이버시 권리

https://www.databricks.com/dataaisummit/speaker/shir-chorev/#

Shir Chorev - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingShir ChorevCTO at DeepchecksBack to speakersShir is the co-founder and CTO of Deepchecks, an MLOps startup for continuous validation of ML models and data. Previously, Shir worked at the Prime Minister’s Office and at Unit 8200, conducting and leading research in various Machine Learning and Cybersecurity related challenges. Shir has a B.Sc. in Physics from the Hebrew University, which she obtained as part of the Talpiot excellence program, and an M.Sc. in Electrical Engineering from Tel Aviv University. Shir was selected as a featured honoree in the Forbes Europe 30 under 30 class of 2021.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/ganesh-deivarayan

Ganesh Deivarayan - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingGanesh DeivarayanSr Manager at American AirlinesBack to speakersCurrently leading the TechOps Data Strategy and Cloud Engineering StrategyLooking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/dataaisummit/speaker/marianna-cervino/#

Marianna Cervino - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingMarianna CervinoGlobal Data Scientist at GucciBack to speakersMarianna holds a Master Degree in Physics from University of Bari. She is a Data Scientist experienced in Time Series Forecasting methodologies and has worked on business problems of diverse industries in the past years. She joined Gucci in 2021, where she works in collaboration with the Media Department.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.

https://www.databricks.com/jp/discover/beacons

Beacons Hub Page | DatabricksSkip to main contentPlatformThe Databricks Lakehouse PlatformDelta LakeData GovernanceData EngineeringData StreamingData WarehousingData SharingMachine LearningData SciencePricingMarketplaceOpen source techSecurity and Trust CenterWEBINAR May 18 / 8 AM PT Goodbye, Data Warehouse. Hello, Lakehouse. Attend to understand how a data lakehouse fits within your modern data stack. Register nowSolutionsSolutions by IndustryFinancial ServicesHealthcare and Life SciencesManufacturingCommunications, Media & EntertainmentPublic SectorRetailSee all IndustriesSolutions by Use CaseSolution AcceleratorsProfessional ServicesDigital Native BusinessesData Platform MigrationNew survey of biopharma executives reveals real-world success with real-world evidence. See survey resultsLearnDocumentationTraining & CertificationDemosResourcesOnline CommunityUniversity AllianceEventsData + AI SummitBlogLabsBeaconsJoin Generation AI in San Francisco June 26–29   Learn about LLMs like Dolly and open source Data and AI technologies such as Apache Spark™, Delta Lake, MLflow and Delta SharingExplore sessionsCustomersPartnersCloud PartnersAWSAzureGoogle CloudPartner ConnectTechnology and Data PartnersTechnology Partner ProgramData Partner ProgramBuilt on Databricks Partner ProgramConsulting & SI PartnersC&SI Partner ProgramPartner SolutionsConnect with validated partner solutions in just a few clicks.Learn moreCompanyCareers at DatabricksOur TeamBoard of DirectorsCompany BlogNewsroomDatabricks VenturesAwards and RecognitionContact UsSee why Gartner named Databricks a Leader for the second consecutive yearGet the reportTry DatabricksWatch DemosContact UsLoginJUNE 26-29REGISTER NOWDatabricks Beacons ProgramThe Databricks Beacons program is our way to thank and recognize the community members, data scientists, data engineers, developers and open source enthusiasts who go above and beyond to uplift the data and AI community.Whether they are speaking at conferences, leading workshops, teaching, mentoring, blogging, writing books, creating tutorials, offering support in forums or organizing meetups, they inspire others and encourage knowledge sharing – all while helping to solve tough data problems.Meet the Databricks BeaconsBeacons share their passion and technical expertise with audiences around the world. They are contributors to a variety of open source projects including Apache Spark™, Delta Lake, MLflow and others. Don’t hesitate to reach out to them on social to see what they’re working on.ISRAELAdi PolakAdi is a Senior Software Engineer and Developer Advocate in the Azure Engineering organization at Microsoft.FRANCEBartosz KoniecznyBartosz is a Data Engineering Consultant and an instructor.  UNITED STATESR. Tyler CroyTyler, the Director of Platform Engineering at Scribd, has been an open source developer for over 14 years.CHINAKent YaoKent is an Apache Spark™ committer and a staff software engineer at NetEase.IRELANDKyle HamiltonKyle is the Chief Innovation and Data Officer at iQ4, and a lecturer at the University of California, Berkeley.POLANDJacek LaskowskiJacek is an IT freelancer who specializes in Apache Spark™, Delta Lake and Apache Kafka.UNITED STATESScott HainesScott is a Distinguished Software Engineer at Nike where he helps drive Apache Spark™ adoption.UNITED KINGDOMSimon WhiteleySimon is the Director of Engineering at Advancing Analytics, is a Microsoft Data Platform MVP and Data + AI Summit speaker.UNITED STATESGeeta ChauhanGeeta leads AI/PyTorch Partnership Engineering at Facebook AI and focuses on strategic initiatives.SWITZERLANDLorenz WalthertLorenz Walthert is a data scientist, MLflow contributor, climate activist and a GSoC participant.CANADAYitao LiYitao is a software engineer at SafeGraph and the current maintainer of sparklyr, an R interface for Apache Spark™.POLANDMaciej SzymkiewiczMaciej is an Apache Spark™ committer. He is available for mentoring and consulting.JAPANTakeshi YamamuroTakeshi is a software engineer, Apache Spark™ committer and PMC member at NTT, Inc., who mainly works on Spark SQL.Membership CriteriaBeacons are first and foremost practitioners in the data and AI community whose technology focus includes MLflow, Delta Lake, Apache Spark™, Databricks and related ecosystem technologies. Beacons actively build others up throughout the year by teaching, blogging, speaking, mentoring, organizing meetups, creating content, answering questions on forums and more.Program BenefitsPeer networking and sharing through a private Slack channelAccess to Databricks and OSS subject matter expertsRecognition on the Databricks website and social channelsCustom swagIn the future, sponsored travel and lodging to attend select Databricks eventsSponsorship and swag for meetupsNominate a peerWe’d love to hear from you! Tell us who made continued outstanding contributions to the data and AI community. Candidates must be nominated by someone in the community, and everyone — including customers, partners, Databricks employees or even a current Beacon — is welcome to submit a nomination. Applications will be reviewed on a rolling basis, and membership is valid for one year.NominateProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoProductPlatform OverviewPricingOpen Source TechTry DatabricksDemoLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunityLearn & SupportDocumentationGlossaryTraining & CertificationHelp CenterLegalOnline CommunitySolutionsBy IndustriesProfessional ServicesSolutionsBy IndustriesProfessional ServicesCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsCompanyAbout UsCareers at DatabricksDiversity and InclusionCompany BlogContact UsSee Careers at DatabricksWorldwideEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. All rights reserved. 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https://www.databricks.com/br/product/data-lakehouse

Data Lakehouse Platform da Databricks - Agende uma demonstração!Skip to main contentPlataformaDatabricks Lakehouse PlatformDelta LakeGovernança de dadosData EngineeringStreaming de dadosArmazenamento de dadosData SharingMachine LearningData SciencePreçosMarketplaceTecnologia de código abertoCentro de segurança e confiançaWEBINAR Maio 18 / 8 AM PT Adeus, Data Warehouse. Olá, Lakehouse. Participe para entender como um data lakehouse se encaixa em sua pilha de dados moderna. Inscreva-se agoraSoluçõesSoluções por setorServiços financeirosSaúde e ciências da vidaProdução industrialComunicações, mídia e entretenimentoSetor públicoVarejoVer todos os setoresSoluções por caso de usoAceleradores de soluçãoServiços profissionaisNegócios nativos digitaisMigração da plataforma de dados9 de maio | 8h PT   Descubra a Lakehouse para Manufatura Saiba como a Corning está tomando decisões críticas que minimizam as inspeções manuais, reduzem os custos de envio e aumentam a satisfação do cliente.Inscreva-se hojeAprenderDocumentaçãoTreinamento e certificaçãoDemosRecursosComunidade onlineAliança com universidadesEventosData+AI SummitBlogLaboratóriosBeaconsA maior conferência de dados, análises e IA do mundo retorna a São Francisco, de 26 a 29 de junho. ParticipeClientesParceirosParceiros de nuvemAWSAzureGoogle CloudConexão de parceirosParceiros de tecnologia e dadosPrograma de parceiros de tecnologiaPrograma de parceiros de dadosBuilt on Databricks Partner ProgramParceiros de consultoria e ISPrograma de parceiros de C&ISSoluções para parceirosConecte-se com apenas alguns cliques a soluções de parceiros validadas.Saiba maisEmpresaCarreiras em DatabricksNossa equipeConselho de AdministraçãoBlog da empresaImprensaDatabricks VenturesPrêmios e reconhecimentoEntre em contatoVeja por que o Gartner nomeou a Databricks como líder pelo segundo ano consecutivoObtenha o relatórioExperimente DatabricksAssista às DemosEntre em contatoInício de sessãoJUNE 26-29REGISTER NOWPlataforma Databricks LakehouseCombine seu data warehousing e casos de uso de IA em uma única plataformaExperimente gratuitamenteAgendar uma demonstração WEBINAR • Goodbye, Data Warehouse. Hello, Lakehouse. Attend on May 18 and get a $100 credit toward a Databricks certification course Register nowSimples. Aberta. Multicloud.A Plataforma Databricks Lakehouse combina o melhor dos data lakes e data warehouses para entregar a confiabilidade, governança reforçada e desempenho de data warehouses com a abertura, flexibilidade e suporte a machine learning de data lakes.Essa abordagem unificada simplifica sua stack de dados moderna ao acabar com silos que tradicionalmente separam e complicam as áreas de engenharia de dados, análise, BI, data science e a machine learning. Ela é baseada em padrões abertos e código aberto para maior flexibilidade. Esta estratégia comum para gerenciamento de dados, segurança e governança ajuda você a operar com mais eficiência e inovar mais rapidamente.SimplesA abordagem unificada simplifica sua arquitetura de dados ao acabar com silos que tradicionalmente separam as áreas de análise, BI, data science e machine learning. Com um lakehouse, é possível eliminar a complexidade e as despesas que impedem você de atingir todo o potencial das suas iniciativas de análise e IA.AbertaO Delta Lake é a fundação aberta do lakehouse, entregando confiabilidade e desempenho recordes diretamente nos dados no data lake. Ele permite evitar estruturas proprietárias, compartilhar dados facilmente e criar sua stack de dados moderna com acesso irrestrito ao ecossistema de projetos de dados de código aberto e à ampla rede de parceiros da Databricks.Saiba mais sobre mais de 450 parceiros em todo o cenário de dadosSaiba MaisMulticloudA Plataforma Databricks Lakehouse oferece uma experiência consistente de gerenciamento, segurança e governança em todas as nuvens. Não há necessidade investir e de reinventar processos para cada plataforma de nuvem que você usa para suportar seus projetos de dados e IA. Em vez disso, suas equipes de dados podem se concentrar em colocar todos os seus dados para trabalhar e descobrir novos insights.Saiba MaisSblocca il potenziale dei tuoi dati e dei tuoi team di datiScopri di più su come Databricks Lakehouse Platform abilita i tuoi carichi di lavoro di dati e intelligenza artificialeData EngineeringDatabricks SQLMachine leaningConteúdo relacionado Todos os recursos de que você precisa. Reunidos em um só lugar. Explore nossa biblioteca de recursos: você encontrará e-books e vídeos sobre os benefícios de utilizar Databricks para data engineering . Explorar recursosLakehouseO que é lakehouse?Livro para leigos: The Modern Cloud Data PlatformA ascensão do paradigma lakehouseAscensão do Data Lakehouse por Bill Inmon, pai do data warehouseDelta Lakee-book: The Big Book of Data EngineeringDelta Lake: O Guia Definitivo por O'ReillyGuia definitivo do Delta LakeDelta Lake: a fundação do seu lakehouseMachine leaninge-book: Standardizing the ML LifecycleEvento virtual: Criação de plataformas de machine learningTudo pronto para começar?Experimente o Databricks gratuitamenteProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoProdutoVisão geral da plataformaPreçosTecnologia de código abertoExperimente DatabricksDemoAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineAprendizagem e suporteDocumentaçãoGlossárioTreinamento e certificaçãoCentral de ajudaInformações legaisComunidade onlineSoluçõesPor setorServiços profissionaisSoluçõesPor setorServiços profissionaisEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoEmpresaQuem somosCarreiras em DatabricksDiversidade e inclusãoBlog da empresaEntre em contatoSee Careers at DatabricksMundialEnglish (United States)Deutsch (Germany)Français (France)Italiano (Italy)日本語 (Japan)한국어 (South Korea)Português (Brazil)Databricks Inc. 160 Spear Street, 13th Floor San Francisco, CA 94105 1-866-330-0121© Databricks 2023. 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https://www.databricks.com/dataaisummit/speaker/yali-sassoon

Yali Sassoon - Data + AI Summit 2023 | DatabricksThis site works best with JavaScript enabled.HomepageSAN FRANCISCO, JUNE 26-29VIRTUAL, JUNE 28-29Register NowSession CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingYali SassoonCPO at SnowplowBack to speakersYali is passionate about the transformative impact of data. Yali Sassoon co-founded Snowplow to help companies realize the possibilities the behavioral data creates to build deep understanding of individuals in real-time. Prior to Snowplow Yali spent his career in data, as a consultant (operational and strategic) and in house at OpenX. Yali has an MPhil in History and Philosophy of Science and a BA in Natural Sciences, both from the University of Cambridge.Looking for past sessions?Take a look through the session archive to find even more related content from previous Data + AI Summit conferences.Explore the session archiveRegister today to save your spotRegister NowHomepageOrganized By Session CatalogTrainingSpeakers2022 On DemandWhy AttendSpecial EventsSponsorsAgendaVirtual ExperiencePricingFAQEvent PolicyCode of ConductPrivacy NoticeYour Privacy ChoicesYour California Privacy RightsApache, Apache Spark, Spark, and the Spark logo are trademarks of the Apache Software Foundation. The Apache Software Foundation has no affiliation with and does not endorse the materials provided at this event.