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International Pharmaceutical Manufacturer compares Two Cloud Platforms
– Microsoft Azure & Amazon AWS

International Pharmaceutical Manufacturer compares Two Cloud Platforms – Microsoft Azure & Amazon AWS

International Pharmaceutical Manufacturer compares Two Cloud Platforms – Microsoft Azure & Amazon AWS
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What Next Pathway's International Pharmaceutical Manufacturer Case Study covers

An International Pharmaceutical Manufacturer compared Microsoft Azure and Amazon AWS in just 4 weeks. Next Pathway’s automation platform translated Informatica code to PySpark, converted Oracle code to Postgres and Aurora, and delivered empirical workload testing across both cloud platforms to support enterprise cloud migration decisions.

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Comparative Cloud Platform Evaluation

An international pharmaceutical manufacturer wanted to migrate its Oracle enterprise data warehouse and Informatica data pipelines to the cloud but needed to determine which platform would best support its workloads. Next Pathway built and tested both AWS and Azure environments to provide measurable performance and operational comparisons.

Automated Code Translation and QA Environments

Using the SHIFT Migration Suite, Next Pathway converted Informatica code to PySpark and translated Oracle code to Postgres and Aurora. Integrated QA environments were created on both Microsoft Azure and Amazon AWS where translated code and test data were executed and validated.

Data Driven Cloud Migration Strategy

Both translated code sets were executed across Azure and AWS to generate comparative workload results for the client. Within 4 weeks, the organization received empirical evidence identifying which workloads were best suited for each platform, enabling a more customized and efficient enterprise cloud migration strategy.

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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
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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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