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Teradata to Azure Synapse Analytics Cloud Migration Checklist

A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to Teradata to Azure Synapse Analytics faster and with full confidence.

Teradata to Azure Synapse Analytics Cloud Migration Checklist (1)
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Teradata to Azure Synapse Analytics

A successful Teradata to Azure Synapse Analytics Cloud migration requires a structured, phase by phase approach across discovery, code translation, validation, and cutover. Next Pathway's Teradata to Azure Synapse Analytics 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 Discovery

Discover Teradata database objects, ETLs, dependencies, and downstream systems to define migration scope and priorities. Identify compatibility issues early and document the target Azure Synapse environment for a smoother migration.

Database Migration and Translation

Identify workloads, prioritize migration waves, and define the code objects included in each phase of execution. Clear workload prioritization ensures translation activities are completed in the right sequence and aligned to business goals.

Validate that all required code and ETL processes are fully accounted for before migration begins. Teams should determine whether ETL pipelines will be migrated or modernized to support long term cloud objectives.

Testing

Develop a complete testing strategy early in the migration project to support workload prioritization and validation. Business stakeholders should participate in test case development to ensure success criteria are clearly defined.

Use automation wherever possible to streamline CI/CD pipelines and accelerate validation activities. Thorough testing before cutover helps reduce migration risk and improve cloud readiness.

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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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