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Modernizing a Global Luxury Brand’s Data Platform: From IBM DB2 & SQL Server to Snowflake & DBT

Building a unified Snowflake data platform from legacy IBM DB2, SQL Server, CDM, and Talend environments. 

Modernizing a Global Luxury Brand’s Data Platform From IBM DB2 & SQL Server to Snowflake & DBT
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What Next Pathway's Global Luxury Brand Case Study Covers

A Global Luxury Brand modernized IBM DB2, SQL Server, Cognos Data Manager, and Talend to Snowflake and DBT in 12 months. Next Pathway’s automation platform translated 6,000+ legacy objects, converted CDM and Talend ETL workloads to DBT, and delivered a scalable cloud native data platform built for advanced analytics and AI. 

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Legacy Platform Modernization

The customer needed to modernize a fragmented environment spanning IBM DB2, SQL Server, Cognos Data Manager, Talend, and custom SQL scripts. Next Pathway translated more than 6,000 legacy objects and migrated databases and ETL workloads to Snowflake and DBT within a 12 month transformation program. 

Automated ETL and SQL Conversion

Next Pathway converted Cognos Data Manager ETL jobs to DBT and Linux shell scripts while repointing Talend workloads to Snowflake and translating them to DBT. Proprietary SQL incompatibilities were resolved through automated translation and targeted remediation to ensure Snowflake compatibility. 

Cloud Native Foundation for Analytics and AI

The modernization delivered a unified Snowflake based data platform with modular DBT transformations and scalable data access across business units. The new architecture improved analytics performance, reduced dependency on legacy technologies, and established a foundation for future AI, machine learning, and real time analytics initiatives. 

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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
British Asset Management Firm Migrates from Azure Synapse and Azure Data Factory to_Cover

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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