Migration Assurance Package
Apply proven, structured approaches and risk mitigation
strategies to help ensure seamless migrations to theDatabricks Lakehouse Platform

Business challenge
Businesses are moving at an ever-increasing pace to stay ahead of the game,requiring their IT organizations to vet and deploy modern architectures andtechnology platforms to help drive business outcomes. IT is driven to lead with
innovation — focusing on strategic priorities vs. operating in keep-the-lightson mode. That’s why more than 7,000 organizations worldwide — including ABN
AMRO, Condé Nast, H&M Group, Regeneron and Shell — rely on Databricks tomodernize all their data, analytics and AI. You need to steer the best path forward
in migrating siloed data marts and data warehouses, legacy Hadoop and SAS
systems to unleash innovation while minimizing risk and cost. The Databricks
Migration Assurance package can help.

Customer benefits andvalue realizationI ncreased productivity andfaster time to insightsB est price/performanceU nified architecture andgovernance, lower TCON o more upgrade hassles
U nlock new ML/AI use casesExecutive summaryS implified architecture

The Databricks Migration Assurance package gives you a concrete migration
outcome through a prescriptive approach that maximizes the value of your existingdata and pipeline investments — ensuring seamless migration to the DatabricksN o lock-in to aging hardwareF uture-proof platform, novendor lock-in

Lakehouse Platform and best practices conformance while reducing risk andcost. Databricks subject matter experts work as part of your team providing
architecture, planning, design and ongoing expert support and technicalguidance in the form of an advisory capacity throughout the migration journey
to ensure success.

Out of scopeC onfiguration and integration ofnon-Databricks products andsystems

Lakehouse Platform
BusinessIntelligence

SQLAnalytics

Governance and Security
Table ACLs

DataWarehousing

DataEngineering

Data
Streaming

Data Swienwr
and MLUnity Catalog

Fine-grained governance for data and AI

Data Scienc eand ML

Governance and Security
Files and Blobs

Delta Lake

Data reliaility and $erforance

Data Warehouse
Structured ta£lesCloud Data LakeAll structured and unstructured dataDatòStreaêing

Data La®eUnstructered files:
logs, text, images, video

Challenges with siloed data marts and data warehouses, Hadoop and SAS
Cost and complexity

Data and AI teams are siloedInnovation slowed as ML and predictive insights are notnatively integrated

Compute and storage couplingHeavy focus on platform administration

Missed opportunity

Inflexible clusters and sizing

Databricks migration services implementation methodology

Migration readiness

Integration and testingReview use case requirements

Review and help design use cases

Migration assessment workshop

Review and help configure data sources

Procedural migration plan and checklist

Review and help with integrations

Architecture review and design

ML/AI model reviews and data validation

Use case development workshops

Platform optimizations

Historical data and code migration

Documentation and closeout

Oversee migration execution

Documentation finalization

Review and help execute historical data migration

Documentation review and turnover

Review and help execute code migration

Project close checklist

Review and configure existing data sources to theDatabricks Lakehouse Platform

Single point of technical contact in the future

Tiering and schedule
SILVER*
2–3 months
 igration readinessMHistorical data and code migration
Integration and testingDocumentation and closeoutGOLD*
5–6 months
 igration readinessMHistorical data and code migration
Integration and testingDocumentation and closeout

PLATINUM*
12–18 months
 igration readinessMHistorical data and code migration
Integration and testingDocumentation and closeout*U p to 2 resources supporting the activities over a specified duration per a given tier. The core activities performed are the same across different tiers; however, theduration of engagement is longer for higher tiers, as they tackle increasingly larger scope and higher complexity.

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