Jumpstart Package
Summary
The Databricks Unified Data Analytics Platform enables your data and AI team to holistically analyze data from data warehouses,
data lakes and other data stores by utilizing a single engine for batch, ML, streaming and real-time queries. By unifying data
science and engineering on a shared cloud-native platform with collaborative notebooks and complete ML lifecycle support, you
are now ready to tackle your toughest data problems. So what’s the quickest way to get started? And how do you onboard yourteam members and support key users applying best practices?
The Databricks Jumpstart packaged offerings help you accelerate your project
timelines by familiarizing you with the Databricks platform and key capabilities that
follow best practices. You work with our industry-leading experts from the Databricks
Professional Services team. The offerings reflect the most common questions ourcustomers face during their early Databricks journey and provide you with a path forsuccessful adoption.

Resources and schedule
Jumpstart*
2 weeks
Getting users up and running
Architecture best practices

Key outcomes

High-level review of use cases

General onboarding: environmental setup, administration and user provisioning
Familiarization with Databricks and key features
A reference architecture for your use cases and associated best practices
D ATA L A K E

Define and design a referencearchitecture
ETL pipeline/Spark
performance optimization
and best practices

MODEL LIFECYCLE MANAGEMENT

Reproducible
Experiments
Serialized Models

Reference
DataTables

Feature Store

Streaming +Batch Jobs

E X P L O R AT O R Y
A N A LY S I S

MLﬂow Tracking Server

MODEL
TRAINING

Notebooks

Landing / Raw
TablesReﬁnedTablesTransformations

Enrichments

MODEL
DEPLOYMENTStreaming +Batch Jobs

EnrichedTables

Best practices workshops
on security, DevOps andother topics

Feature Eng

Out of scope
Data cleansing associated withbuilding a broader data lake
Implementation deliverables

D ATA B R I C K S R U N T I M E
SparkClusters

Single Node
Data Science

GPU Access

D ATA B R I C K S F I L E S Y S T E M / S 3 / B L O B* 1 Senior Consultant supporting theactivity over a 2-week sprint1

Overview
The offerings focus on general onboarding best practices workshops for security, DevOps and special use cases, project planningand use case review sessions with high-level architecture guidance and recommendations on best practices. They are designed
for first-time platform deployments and new use cases. And can also be used by existing customers with a new phase in their
Databricks journey or lifecycle. See the Resources and schedule section for details.

Key benefits
Shorter time to value				Accelerated project timelines			Streamlined onboarding
Increased agility with reusable design and reference architecture

Databricks Jumpstart workflow
FA M I L IAR IZ AT IO N
W I T H DATAB R ICKSA DM INISTR ATIONE TL AND S PAR K

Workspace
setup, notebook
collaboration

User groups,
just-in-time user
provisioning

Job schedulingsettings,
alerts, cluster
configuration

Notebook, cluster
permissions, IAM
Policy accessSparkfundamentals,
Delta andoptimizations
Performancetuning basics(partitions/tasks)

E N V I R ON M E N T
S E TU PR E F ERE N C E
AR CH I T E CT U RE

Integration,
job deployment
options

Referencearchitecture foryour use cases

Librarymanagement
for clusters

Implementation
guidance© Databricks Inc. 2021. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation. Privacy Policy | Terms of Use