British Asset Management Firm Migrates from Azure Synapse and Azure Data Factory to Snowflake
A strategic modernization journey from Azure Synapse and Azure Data Factory to a unified Snowflake data platform.
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 British Asset Management Firm Case Study Covers
A British Asset Management Firm migrated Azure Synapse and Azure Data Factory to Snowflake. Next Pathway’s automation platform delivered 100% automated code translation and migration, completed the project in 10 months, and automated QA and data validation.
Unified Data Platform and Simplified Operations
The firm successfully migrated all Azure Synapse and Data Factory workloads to Snowflake, consolidating multiple environments into a unified data platform. This eliminated legacy cloud silos, simplified IT management, and reduced operational overhead.
Automated Migration with Business Continuity
Next Pathway used SHIFT Cloud to automate code and pipeline conversion to Snowflake while Analyzer Reports delivered full inventory and risk analysis. Automated QA and validation accelerated testing and ensured uninterrupted business operations and compliance throughout the migration.
Foundation for AI and Advanced Analytics
The new Snowflake platform enabled real time analytics and reporting while positioning the company for future AI adoption and improved risk management. The modernized architecture supports scalable analytics workloads and faster executive insights with strong governance and operational efficiency.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
80%
Faster time-to-market for AI-ready infrastructure
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A global financial services leader modernized Teradata, DataStage, Informatica, and Talend to Snowflake, completing the migration in 10 months with minimal business disruption.
Read the case study to see how Next Pathway delivered:
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Download the case study to learn how a global financial services leader modernized Teradata, DataStage, Informatica, and Talend to Snowflake, creating a unified cloud platform for analytics, AI, and future growth.
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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