Fortune 500 Financial Services Company migrates their Legacy Netezza data warehouse, SSIS, DataStage and Informatica
pipelines to Snowflake
Fortune 500 Financial Services Company migrates their Legacy Netezza data warehouse, SSIS, DataStage and Informatica pipelines to Snowflake
Next Pathway is an Elite Snowflake Partner, trusted by global enterprises to deliver end-to-end modernization, from deep discovery to production cutover.
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What Next Pathway's Fortune 500 Financial Services Company Case Study covers
A Fortune 500 Financial Services Company migrated a Netezza data warehouse along with ETL pipelines to Snowflake in just 6 months. Next Pathway’s automation platform delivered 100% translation of more than 600,000 lines of Netezza code, repointed thousands of ETL pipelines to Snowflake, and enabled retirement of the legacy enterprise data warehouse environment.
Large Scale Netezza to Snowflake Migration
Next Pathway migrated the company’s legacy Netezza enterprise data warehouse to Snowflake as part of a large scale cloud modernization initiative. The migration also included complex ETL pipelines built using DataStage, Informatica, and SSIS across a federated enterprise environment.
Automated Translation and ETL Repointing
Using the SHIFT Migration Suite, Next Pathway completed 100% translation of more than 600,000 lines of Netezza code to Snowflake over a 24 week engagement. The project also repointed thousands of ETL pipelines, updated embedded SQL logic, and modified all connection parameters for Snowflake compatibility.
Accelerated Snowflake Modernization
Next Pathway converted BI report SQL queries and repointed reporting workloads from the legacy Netezza platform to Snowflake. Within 6 months, the client successfully retired the legacy data warehouse, modernized ETL operations, and established a scalable Snowflake based analytics environment.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
80%
Faster time-to-market for AI-ready infrastructure
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What Industry Analysts Say
Rob Enderle
ENDERLE GROUP
Eric Kavanagh
THE BLOOR GROUP
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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