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Global Automotive Company Migrates From Netezza and
Hadoop to Snowflake

Global Automotive Company Migrates From Netezza and Hadoop to Snowflake

Global Automotive Company Migrates From Netezza and Hadoop to Snowflake
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What Next Pathway's Global Automotive Company Case Study Covers

A Global Automotive Company migrated Netezza and Hadoop to Snowflake. Next Pathway’s automation platform translated 100% of Netezza SQL code in 4 weeks, accelerated cloud data consumption speeds by 38%, and enabled secure self service access across cloud environments.

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Netezza to Snowflake Modernization

The customer’s Netezza enterprise data warehouse was approaching end of life after IBM halted support for the platform. Next Pathway translated 250,000 lines of Netezza SQL code to Snowflake with a full 4 Point QA process completed in 4 weeks.

Hadoop Data Lake Migration

The customer’s Hadoop Data Lake contained approximately 130 TB of historical data with annual growth of 50%. Next Pathway developed an automated data replication mechanism to move data from on premise Hadoop environments to cloud targets through a self service capability.

Hybrid Cloud Data Consumption

The migration required a framework that enabled hundreds of business users to securely consume cloud data across multiple BI and analytics tools. Next Pathway created a hybrid cloud platform that met regulatory requirements and improved cloud data consumption speeds by 38%.

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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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