Leading Fintech Provider Migrates Informatica PowerCenter and Netezza to IDMC and Snowflake
Modernizing Informatica PowerCenter and Netezza with a seamless transition to Informatica IDMC and Snowflake, enabling scalable data integration and cloud-native analytics.
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 Leading Fintech Provider Case Study covers
A Leading Fintech Provider migrated Informatica PowerCenter and Netezza to IDMC and Snowflake. Next Pathway's automation platform delivered migration of 11,000 Netezza objects, conversion of 8,000 Informatica PowerCenter objects, and project completion within six months.
Accelerated Cloud Modernization
Next Pathway delivered a complete cloud modernization initiative within six months without disrupting business operations. Automated migration workflows reduced manual effort and accelerated project timelines.
Large Scale Automated Conversion
The migration included conversion of 8,000 Informatica PowerCenter objects to IDMC and migration of 11,000 Netezza objects to Snowflake. Automation improved consistency, reduced project risk, and increased testing accuracy across the environment.
Improved Scalability and Cost Efficiency
The transition from ETL to ELT improved scalability and analytics performance. Moving to Snowflake enabled a cloud native pay as you go model that reduced infrastructure costs and increased operational flexibility.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
80%
Faster time-to-market for AI-ready infrastructure
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ENDERLE GROUP
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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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