HOME SERVICES TECHNOLOGIES VENDORS CUSTOMERS TEAM WORKSHOPS HADOOP JOBS – WE’RE HIRING CONTACT BLOG ANNOUNCING BIG DATA WORKSHOPS DOING HADOOP SECURELY BELGA TESTIMONIAL – LEARN MORE HADOOP FOR DATA WAREHOUSE OFFLOAD WE’RE HIRING! CLICK FOR DETAILS Hadoop & Big Data Consulting OUR MARKET LEADING, EXPERT TEAM OF CERTIFIED BIG DATA CONSULTANTS DESIGNS, DEVELOPS AND DEPLOYS ADVANCED BIG DATA APPLICATIONS AND ANALYTICS SOLUTIONS. Innovation Big Industries offers structured discovery, strategy & planning exercises as short workshops formulated to help inform and engage enterprise stakeholders. Learn more about our workshops Proof of Concept Big Industries blends industry leading experience in Big Data technologies to define the optimal foundation for next generation, mature and enterprise ready information processing applications. More Implementation Services Big Industries focuses on developing Big Data and Big Compute solutions that deliver foundation business value early while incrementally adding advanced features over time. Learn more about our Hadoop Rapid Start Services Big Data Analytics Big Industries offers data science consulting in order to help organisations to operationalise their big data. Our consultants are experienced in using leading Big Data statistics, analytics & machine learning suites like Revolution R Enterprise and Apache Spark. More Technologies EXCELLENCE IN BIG DATA Hadoop cluster compute platform The Apache™ Hadoop® project develops open-source software for reliable, scalable, distributed computing. Hadoop is an open-source software framework for storing and processing big data in a distributed fashion on large clusters of commodity hardware. Essentially, it accomplishes two tasks: massive data storage and faster processing. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the stack itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. Spark parallel compute framework Apache Spark is a fast and general-purpose cluster computing system which integrates with Apache Hadoop and the Hadoop YARN cluster resource management system. It supports a rich set of high-level tools including Spark SQL for SQL query based structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for near real time datastream processing. SolrCloud distributed search Solr is a blazing fast open source enterprise search platform. Its features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world’s largest internet sites. Apache Solr includes the ability to set up a cluster of Solr servers that combines fault tolerance and high availability, integrated with the Apache Hadoop cluster compute platform. Called SolrCloud, these capabilities provide distributed indexing and search capabilities. Impala realtime SQL engine The Apache-licensed Impala project brings interactive querying and massively parallel data warehouse technology to Hadoop, enabling users to issue low-latency SQL queries to data stored in HDFS and Apache HBase without requiring data movement or transformation. Impala is integrated with Hadoop to use the same file and data formats, metadata, security and resource management frameworks used by MapReduce, Apache Hive, Apache Pig and other Hadoop software. Kafka parallel message queue Apache Kafka is a free and open source, parallel message queuing infrastructure which integrates with Hadoop. Kafka enables organisations to deploy a Hadoop cluster to function as their central messaging backbone as a flexible alternative to traditional enterprise messaging solutions. Offering elastic and transparent scalability without downtime, message queues are partitioned and spread across a cluster of servers to scale beyond the capability of any single computer. Messages are reliably persisted on disk and replicated within the cluster to prevent data loss and each message broker can handle terabytes of messages with consistent performance. Kafka boasts a modern, cluster-centric design that offers strong durability and fault-tolerance guarantees. HBase distributed db HBase is a NoSQL database. “NoSQL” is a general term meaning the database doesn’t use a SQL query engine as its primary access mechanism. HBase is a highly distributed database storage engine founded on Apache Hadoop. While it lacks many of the features you may find in an RDBMS, HBase has many features that support linear, modular scaling. HBase capacity is expanded by adding commodity class servers. If an HBase cluster is expanded from 10 to 20 servers, for example, it doubles both in terms of storage and processing capacity. Traditional RDBMS can scale well – up to the size of a single server – and often require vendor certified, specialized hardware and storage devices. HBase has delivered horizontal database scalability in deployments worldwide on clusters up to hundreds of servers wide, with no requirement for specialised server architecture, storage array nor fibrechannel. Apache Pig Apache Pig is a high level scripting language and job compiler for analyzing large datasets. Pig programs are capable of running in a highly parallelized manner, which enables them to process very large data sets. Pig’s compiler currently generates sequences of Map-Reduce programs for execution on a Hadoop cluster. The Pig scripting language offers the following benefits: • Ease of programming. It is trivial to achieve parallel execution of simple, “embarrassingly parallel” data analysis tasks. Complex tasks comprised of multiple interrelated data transformations are explicitly encoded as data flow sequences, making them easy to write, understand, and maintain. • Optimization opportunities. The way in which tasks are encoded permits the system to optimize their execution automatically, allowing the user to focus on semantics rather than efficiency. • Extensibility. Pig supports User Defined Functions to support special-purpose processing cases. Apache Hive Apache Hive™ is a batch-oriented data warehousing runtime which simplifies ETL [extract, transform, load] processes on large datasets stored in a Hadoop cluster. Hive offers facilities to apply structure onto this data and query the data using a SQL dialect called HiveQL. Titan distributed graph db Titan is a graph database optimized for storing and querying graph datasets containing up to hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals in real time. Titan is designed to support the processing of graphs so large that they require storage and computational capacities beyond what a single machine can provide. To this end, Titan integrates with the Hadoop HBase and Apache Cassandra NoSQL database storage engines for data persistence. Vendors Cloudera is revolutionizing enterprise data management by offering the first unified Platform for Big Data, an enterprise data hub built on Apache Hadoop™. Cloudera offers enterprises one place to store, process and analyze all their data, empowering them to extend the value of existing investments while enabling fundamental new ways to derive value from their data. Only Cloudera offers everything needed on a journey to an enterprise data hub, including software for business critical data challenges such as storage, access, management, analysis, security and search. As the leading educator of Hadoop professionals, Cloudera has trained over 20,000 individuals worldwide. www.cloudera.com learn more MapR delivers on the promise of Hadoop with a proven, enterprise-grade platform that supports a broad set of mission-critical and real-time production uses. MapR brings unprecedented dependability, ease-of-use and world-record speed to Hadoop, NoSQL, database and streaming applications in one unified Big Data platform. MapR is used across financial services, retail, media, healthcare, manufacturing, telecommunications and government organizations as well as by leading Fortune 100 and Web 2.0 companies. www.mapr.com Since 2007 Revolution Analytics has worked to foster growth and learning within the R Community, as well as actively supporting the needs of the increasing ranks of commercial users. Our flagship Revolution R software and services suite, is the innovative leader in Big Data, enterprise analytics. Powered by the R language, Revolution R is used by enterprises with massive data, performance and multi-platform requirements who need to drive down the cost of Big Data. www.revolutionanalytics.com Platfora is the #1 Big Data Analytics platform built natively on Hadoop and Spark. Platfora enables business users and data scientists to visually interact with petabyte-scale data in seconds, allowing them to work with even the rawest forms of transaction, customer interaction and machine data to find new opportunities and manage risk. Platfora is transforming the way businesses unlock insights, make decisions, and produce better outcomes through the use of its industry-defining Customer Analytics, Security Analytics and Internet of Things solutions. Platfora Big Data Analytics is creating data-driven competitive advantages for leading organizations such as Citi, Sears, AutoTrader, Disney, Edmunds.com, Opower, Riot Games, Vivint and TUI Travel. www.platfora.com Follow us on Twitter "Cloudera is building a new open-source storage engine called Kudu, sources say" #bigdata #bigindustries.be http://t.co/wBhWJfZNsj 2 days ago Three best practices for building successful data pipelines http://t.co/8poKs7A7kO via @Radar #bigindustries.be 2 days ago Introduction to HDFS Erasure Coding in Apache Hadoop http://t.co/OW074JRUPR #bigdata #bigindustries.be 2 days ago RT @Datafloq : Here are 10 Big Data facts that you should know when developing a Big Data strategy http://t.co/ouuZ9EAGDj #BigData http://t. … 3 days ago "Making Apache Spark Testing Easy with Spark Testing Base" #bigdata #bigindustries.be http://t.co/WVzSf67nUC 3 days ago Our Customers WE SERVE CLIENTS ACROSS A BROAD RANGE OF MARKETS INCLUDING TELECOMMUNICATIONS, FINANCIAL SERVICES, MEDIA, LIFE SCIENCE, HEALTHCARE AND INTERNET CONTACT US TODAY TO FIND OUT HOW WE CAN HELP YOU Tom Wuytack, ICT Manager at Belga News Agency Every content professional, but especially journalists, are confronted with a multitude of challenges. In a world where media companies struggle for survival and end users expect tailored news whenever it suits them best, information overload forces one to abandon the traditional journalistic approach towards content handling (FIFO). While text used to be the main trigger for news, nowadays image, video and data are taking over. Providing unique content is key, but much of the valuable data is hardly accessible. Can tools be of any assistance here? Discover the possibilities, the constraints and other key considerations in a real life case at Belga News Agency. During his 14 years experience at Belga the agency as evolved rapidly into a multimedia information broker, whilst closely safeguarding a 24/7 high availability. Continuous innovation has always been crucial and resulted in the last 10 years into several award winning projects. (Datanews ICT award 2005 and 2013; EANA award 2014) Big Industries (member of the Cronos Groep) works together with Belga News Agency to translate their ideas into a workable Big Data solution. The Belga Big Content Platform is a business-to-business content asset management service providing a searchable, aggregated source of live news feeds, public domain media and archives of content. The platform will help find just enough, relevant, and timely content to help content professionals to get the information they require. The platform will aggregate and correlate content across multiple languages – Dutch, English, French, German, and will aggregate, correlate and make sense of content from disparate sources – for example, publicly accessible social media, archive sources, online media properties and other news agencies. The platform is founded on the Cloudera Distribution for Hadoop, release 5.3 and uses the HDFS filesystem, Spark grid computing engine, Titan Distributed Graph, HBase distributed database and Solr search. Additionally, the platform leverages public datasets like Freebase, DBpedia, Wiktionary and Geonames to support semantic text enrichment. Big Industries was selected by Belga News Agency as their partner to design, develop and deploy the solution. Innovation distinguishes between a leader and a follower. — Steve Jobs — The Team OUR PROFESSIONAL TEAM OF BIG DATA CONSULTANTS IS WITH YOU EVERY STEP OF THE WAY. Are you ready to start a conversation? Get in touch with us today. Meet the team Founder View Profile Matthias Vallaey × Matthias Vallaey Founder Matthias is founder of Big Industries and a Big Data Evangelist. He has a strong track record in the IT-Services and Software Industry, working across many verticals. He is highly skilled at developing account relationships by bringing innovative solutions that exceeds customer expectations. In his role as Entrepreneur he is building partnerships with Big Data Vendors and introduces their technology where they bring most value. Skills Business Development & Solution Selling Leadership & People Development Management Partnering: Cloudera and MapR Hadoop IT-Services & Software Industry Connect Email Twitter Linkedin Scroll Down Founder View Profile Rob Gibbon × Rob Gibbon Founder Rob is a technical solutions architect with hands on knowledge of Big Data system design, build and operation. He is frequently involved in customer engagement, solution and product design, project management and of course running technical engineering teams. Rob has gained his experience building solutions in varied domains with organisations ranging from upstart to blue chip and can understand and adapt to varied customer needs. Skills Big Data solution design and assurance Cloudera and MapR Hadoop Integration & deployment planning Data warehouse offload with Hadoop Web-scale applications Certified Information Systems Security Professional CISSP Connect Email Twitter Linkedin Scroll Down Senior Developer View Profile Emre Sevinç × Emre Sevinç Senior Developer Emre is a senior software engineer and project lead with more than 15 years of experience, and a formal background in mathematics and cognitive science. He gained his experience in varied domains such as space industry, biomedical informatics, and e-learning. When he is not busy with developing software intensive solutions for Big Data systems, writing technical documentation, and engaging with the customer, he follows the latest developments in Data Science. Skills Cloudera Certified Developer for Apache Hadoop Spark Scala Linux Semantic Web Natural Language Processing Connect Email Twitter Linkedin Scroll Down Developer View Profile Adnane Khouchlaa × Adnane Khouchlaa Developer Adnane is a professional IT consultant with several years working experience gained with strong focus on big data and data integration. He is keen to employ top-notch technologies like (Hadoop, HBase, Hive, Impala, NOSQL, etc.) to establish effective and powerful data crunching. Likewise, Adnane is daily furthering his Big Data conquest by applying newer application paradigms Skills Cloudera Certified Developer for Apache Hadoop NoSQL Data Analysis Data Crunching Big Data Integration Big Data Visualization Connect Email Twitter Linkedin Scroll Down Developer View Profile Mouzzam Hussain × Mouzzam Hussain Developer Mouzzam is an IT professional with hands on knowledge of Data Engineering. He has a keen interest in developing solutions for Big Data. He has gained working experience in processing and analytics of massive datasets. He has worked on Social Network analytics, graph databases and CDRs (Call Detail Records). He is currently doing research in creating solutions for Getting fast query results on Big Data using compact data representations. Skills Cloudera Certified Developer for Apache Hadoop MapR Certified Hadoop Administrator Data Analytics Social Network Analytics Big Data Solutions Development Connect Email Twitter Linkedin Scroll Down DevOps View Profile Bjorn Claessens × Bjorn Claessens DevOps Having attained a bachelor’s degree in Applied Computer Sciences, Bjorn’s interest in Big Data brought him to Big Industries where he is further expanding his knowledge of Big Data and the Hadoop ecosystem. Bjorn is a Big Data consultant and certified Hadoop developer, with further experience in Hadoop system management. Skills Cloudera Certified Developer for Apache Hadoop MapR Certified Hadoop Developer MapR Certified Hadoop Administrator MapR Certified HBase Developer Big Data system integration Connect Email Twitter Linkedin Scroll Down DevOps View Profile Mathias Spiessens × Mathias Spiessens DevOps Mathias brings skills in Cloudera Hadoop cluster deployment, security hardening and operational management, as well as managing Apache Mesos deployments. When he’s not at hard at work at his desk, you can sometimes find Mathias winning another game of table football as Big Industries’ resident table football champion. Skills Hadoop lockdown and security hardening Cloudera Hadoop deployment Cloudera Hadoop operational management Apache Mesos Connect Email Twitter Linkedin Scroll Down info@bigindustries.be +32 496 57 66 27 Veldkant 33a, 2550 Kontich Contact Googleplus Linkedin Twitter Copyright 2015 Big Industries BE 0807729292 Back to Top