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Global automotive leader migrates from informatica PowerCenter and Netezza to Snowflake

Accelerating the modernization of Netezza data warehousing and Informatica PowerCenter ETL workloads through a seamless migration to Snowflake for enterprise-scale analytics.

Global Automotive Leader migrates from Informatica PowerCenter and Netezza to Snowflake (1)
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What Next Pathway's Global Automotive Leader Case Study covers

A Global automotive leader migrated Informatica PowerCenter and Netezza to Snowflake. Next Pathway’s automation platform delivered faster migration delivery, high accuracy code translation, and accelerated time to value through automated conversion and streamlined testing.

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Faster Migration Delivery

Next Pathway automated the migration of Informatica PowerCenter ETL jobs and Netezza database logic to Snowflake SQL. Automation replaced most manual hand coding, reducing delivery timelines and lowering migration risk.

High Accuracy Code Conversion

SHIFT Cloud translated ETL workflows, stored procedures, and table structures directly into optimized Snowflake SQL. High accuracy code translation minimized post migration issues and reduced the need for rework.

Scalable Cloud Analytics Foundation

The migration enabled a flexible and scalable cloud based data foundation for Service Operations analytics. The organization improved analytics flexibility, reduced ongoing data management costs, and completed the migration with no downtime or lost productivity.

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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
Download Case study
British Asset Management Firm Migrates from Azure Synapse and Azure Data Factory to_Cover

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 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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