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Databricks Data Migration Checklist

A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to Databricks Data Migration faster and with full confidence.

Databricks Data Migration Checklist
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What Next Pathway's Databricks Data Migration Checklist covers

A successful Databricks Data migration requires a structured, phase by phase approach across discovery, code translation, validation, and cutover. Next Pathway's Databricks Data Migration Checklist gives your team a complete roadmap, built on the same automation Next Pathway uses to deliver enterprise migrations end to end.

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Inventory and Migration Planning

Create an inventory of databases, ETL pipelines, and migration objects before execution begins. Identify dependencies, resource constraints, and network requirements to prioritize migration activities efficiently.

Data Migration and Optimization

Define migration activities for historical loads, delta synchronization, and final data movement into Databricks. Select the appropriate Databricks storage services and optimize data transfer performance for large scale workloads.

Validation and Testing

Execute data validation, integrity checks, and full scale migration testing before production deployment. Validate performance, data quality, and migration accuracy to support a stable cloud transition.

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1 Billion+

Lines of code translated automatically

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160+

Enterprise modernizations completed

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80%

Faster time-to-market for AI-ready infrastructure

Latest Databricks Migration Case Study

A multinational insurance and financial services provider accelerated legacy application modernization with Databricks and Delta Lake.

Read the case study to see how Next Pathway delivered:

20+ extract applications migrated in 3 months
Hadoop, Hive, and Oozie workloads modernized
Improved performance and operational efficiency
Lower infrastructure and maintenance costs
DOWNLOAD CASE STUDY
Multinational Insurance and Financial Services Provider migrates legacy systems to Databricks

What Industry Analysts Say

Image (Rob Enderle)
Rob Enderle

ENDERLE GROUP

"Next Pathway is providing a solution that accelerates the migration process, giving organizations a faster route to realizing value from their data."
Eric Kavanagh
Eric Kavanagh

THE BLOOR GROUP

"SHIFT Cloud enables a remarkably swift and robust transition from traditional data warehousing to the cloud."

What a Databricks Data Migration Covers

A successful Databricks data migration requires a structured approach to assessment, workload modernization, validation, and production deployment.

Discovery and dependency mapping

Assess source databases, data warehouses, ETL pipelines, analytics workloads, notebooks, and downstream dependencies to establish a comprehensive migration strategy and identify modernization opportunities.

Code translation and modernization

Migrate data, data engineering pipelines, analytics workloads, and processing frameworks to Databricks while optimizing performance, scalability, and operational efficiency through a unified lakehouse architecture.

Validation and functional parity

Validate migrated data, notebooks, pipelines, and business logic to ensure data accuracy, workload reliability, and equivalent functionality across the Databricks environment.

Production cutover planning

Execute a controlled transition to Databricks with deployment planning, testing, governance controls, rollback procedures, and stakeholder sign-off to minimize business disruption.

Latest Insights on Modernization

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