How to Migrate Legacy Systems to the cloud and become AI-Ready
A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to How to Migrate Legacy Systems to the cloud and become AI-Ready faster and with full confidence.
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What Next Pathway's Migrate Legacy Systems to the Cloud and Become AI Ready Guide covers
A successful legacy systems migration requires a structured, phase by phase approach across discovery, code translation, validation, and cutover. Next Pathway's Migrate Legacy Systems to the Cloud and Become AI Ready Guide gives your team a complete roadmap, built on the same automation Next Pathway uses to deliver enterprise migrations end to end.
Assess Legacy Systems and Define Migration Scope
Evaluate legacy systems, data pipelines, dependencies, and downstream applications before migration begins. NextPathway's CRAWLER360 uses automated discovery and lineage analysis to identify which applications and workloads should move to the cloud.
Translate Applications and Data Pipelines for the Cloud
Migrate applications, ETLs, and legacy code to modern cloud platforms with automated precision. NextPathway's SHIFT automates the translation of millions of lines of code and legacy ETL platforms including SSIS, DataStage, Informatica, and Talend to modern cloud platforms.
Validate Migration and Prepare for AI Readiness
Test migrated applications and data pipelines to confirm workloads execute correctly in the cloud environment. NextPathway's TESTER automates functional testing and validation to accelerate post-migration testing and improve confidence before production deployment, preparing your cloud environment for future AI integration and AI-driven business expansion.
1 Billion+
Lines of code translated automatically
160+
Enterprise modernizations completed
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:
Download Snowflake Case Study
Download the case study to learn how a British asset management firm modernized Azure Synapse and Azure Data Factory to Snowflake while ensuring business continuity and accelerating AI readiness.
What Industry Analysts Say
Rob Enderle
ENDERLE GROUP
Eric Kavanagh
THE BLOOR GROUP
What a structured legacy systems migration covers
A structured legacy migration covers discovery, modernization, validation, and deployment to accelerate cloud adoption and AI readiness.
Assess Legacy Systems and Define Scope
Identify applications, ETL pipelines, dependencies, and workloads before migration begins. CRAWLER360 automates discovery and lineage analysis to uncover dependencies and define migration scope.
Translate Applications and Data Pipelines
Modernize applications, ETL workflows, and legacy code for the cloud. SHIFT automates the translation of legacy platforms such as SSIS, DataStage, Informatica, and Talend, reducing manual effort and risk.
Validate Migration and Enable AI Readiness
Confirm data accuracy and functional performance after migration. TESTER automates testing and validation, helping teams accelerate deployment and establish a trusted foundation for future AI initiatives.
Plan Production Cutover
Prepare for deployment with clear cutover, rollback, and readiness plans. A structured cutover process minimizes disruption and helps teams move to production with confidence.
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