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SSIS to Azure Data Factory
Data Migration Checklist

A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to Amazon Redshift faster and with full confidence.

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What Next Pathway's SSIS to Azure Data Factory Cloud Migration Checklist covers

A successful SSIS to Azure Data Factory Cloud migration requires a structured, phase by phase approach across discovery, code translation, validation, and cutover. Next Pathway's SSIS to Azure Data Factory Cloud Migration Checklist gives your team a complete roadmap, built on the same automation Next Pathway uses to deliver enterprise migrations end to end.

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Assessment and Planning

Create an inventory of ETL workflows, transformations, and dependencies before migration begins. Prioritize workloads by complexity and business importance to support efficient migration waves.

Workflow and Dependency Migration

Rebuild workflows in Azure Data Factory while translating ETL logic, SQL queries, and custom code with automation. Validate external services, database connectivity, and workflow dependencies before deployment.

Testing and Cutover

Execute unit testing, integration testing, and automated data reconciliation to validate migrated workloads. Complete staging validation, production cutover, and post deployment monitoring to support a stable cloud transition.

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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
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.

Latest Insights on Modernization

Cloud Migration Resources

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Google BigQuery Migration Checklist

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Snowflake Data Migration Checklist
Snowflake Data Migration Checklist

A step-by-step checklist for enterprises to ensure a smooth migration to Snowflake.

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Azure Data Migration Checklist
Azure Data Migration Checklist

A step-by-step checklist for enterprises to ensure a smooth migration to Azure Synapse.

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