Fortune 500 Fintech Leader Migrates from Informatica PowerCenter and
Netezza to Informatica Cloud (IDMC) and Snowflake
A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to Snowflake faster and with full confidence.
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 Fintech Leader Case Study covers
A Fortune 500 Fintech Leader migrated Informatica PowerCenter and Netezza to Informatica Cloud (IDMC) and Snowflake as part of a large scale cloud modernization initiative. Next Pathway’s AI Enabled SHIFT platform automated code translation, data ingestion, and performance optimization across 12,000+ objects while improving scalability, accuracy, and testing efficiency.
AI Enabled Migration Automation
Next Pathway used its AI Enabled SHIFT technology to automate code conversion from Informatica PowerCenter to Informatica Cloud IDMC and from Netezza to Snowflake. Automation reduced manual effort, accelerated delivery, and improved migration reliability across a complex enterprise environment.
High Accuracy and Streamlined Validation
The migration included system integration testing execution, defect remediation, and BI repointing and validation services. High accuracy in mapping conversions minimized errors and streamlined testing cycles, helping ensure seamless post migration system performance.
Modernized ELT Architecture on Snowflake
The migration transitioned the client from an ETL to an ELT architecture to unlock Snowflake’s scalability and parallel processing capabilities. The new cloud based model improved efficiency for handling massive data volumes while reducing infrastructure costs.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
80%
Faster time-to-market for AI-ready infrastructure
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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:
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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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