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Global Financial Services Provider Migrates from Teradata to
Snowflake and Amazon Redshift

Global Financial Services Provider Migrates from Teradata to Snowflake and Amazon Redshift

Global Financial Services Provider Migrates from Teradata to Snowflake and Amazon Redshift
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What Next Pathway's Global Financial Services Provider Case Study Covers

A Global Financial Services Provider migrated from Teradata to Snowflake and Amazon Redshift. Next Pathway’s automation platform translated 19 million lines of Teradata SQL and Stored Procedure code, achieved 99% code translation out of the box, and accelerated migration timelines by 72% compared to manual estimates.

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Teradata Migration Assessment

The customer needed to determine which workloads were best suited for Snowflake and which for Amazon Redshift. Powered by CRAWLER360, Next Pathway conducted a 4 week migration assessment to identify end to end data lineage, hot and cold spots, and optimization opportunities.

Large Scale Teradata Translation

The customer’s Teradata environment included 19 million lines of SQL and Stored Procedure code, nearly 2 petabytes of historical data, and more than 2,200 data sources. Using SHIFT, Next Pathway achieved 99% translation out of the box across both Snowflake and Amazon Redshift.

Faster Cloud Migration Execution

After migration execution began, Next Pathway achieved 100% translation of all Teradata SQL and Stored Procedures in 4 weeks. The automated migration process accelerated delivery timelines by 72% compared to earlier manual estimates.

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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
Snowflake Modernization Guide

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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