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International Client Migrates their Core Mainframe from IBM DB2 to Microsoft Azure and Databricks

International Client Migrates their Core Mainframe from IBM DB2 to Microsoft Azure and Databricks

International Client Migrates their Core Mainframe from IBM DB2 to Microsoft Azure and Databricks
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What Next Pathway's International Client Case Study covers

An International Client migrated its core mainframe from IBM DB2 to Microsoft Azure and Databricks in just 6 months. Next Pathway’s automation platform translated approximately 300 complex IBM DataStage ETL jobs to PySpark and Databricks in 3 weeks, captured end to end dependency lineage for migration planning, and validated a scalable cloud modernization strategy for the full enterprise migration.

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Core Mainframe Modernization

The client needed to migrate its IBM DB2 based core mainframe to a Microsoft Azure and Databricks native environment to modernize analytics capabilities and eliminate the high operational costs of maintaining the legacy mainframe platform. The migration also involved thousands of undocumented IBM DataStage ETL jobs that increased project complexity.

Automated Dependency Analysis and Code Translation

Next Pathway used CRAWLER360 to capture end to end job dependencies and lineage to finalize migration waves and testing strategies. Using SHIFT, the team translated approximately 300 complex DataStage ETL jobs to PySpark and Databricks within 3 weeks, while TESTER validated the translated workloads using sample data.

Azure and Databricks Migration Validation

Next Pathway refined the target architecture to maximize Microsoft Azure and Databricks capabilities and validated the overall migration strategy through a Phase 0 engagement. The successful validation gave the client confidence that the full mainframe migration could be completed within the required 6 month timeframe.

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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 Snowflake Case Study

Next Pathway helped a UK-based asset management leader migrate from Azure Synapse and Azure Data Factory to Snowflake with zero business disruption and 100% automated code translation.

Read the case study to see how Next Pathway delivered:

End-to-end migration completed in just 10 months
100% automated code translation with SHIFT
Seamless compliance and financial reporting throughout cutover
Real-time analytics and AI-ready data on a unified platform
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What Industry Analysts Say

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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 structured Snowflake migration covers

A successful migration to Snowflake requires a clear plan across four disciplines.

Discovery and dependency mapping

Every code object, ETL pipeline, and data dependency needs to be identified and documented before migration begins. Hidden complexity discovered mid-migration creates delays and risk.

Code translation and modernization

Legacy SQL, stored procedures, and ETL pipelines must be converted into optimized, Snowflake-native workloads. Automated translation eliminates manual rework and ensures full coverage.

Validation and functional parity

Every migrated workload must be validated against the legacy source to confirm data accuracy and functional equivalence before cutover. 100% parity is not optional.

Production cutover planning

Cutover requires a defined plan covering resource allocation, rollback decisions, and business sign-off. Teams that plan cutover from the start move faster and with greater confidence.

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