The Seven Phases of Every Migration
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A proven, phase-by-phase framework for migrating your legacy EDW, Data Lake, and ETL pipelines to The Seven Phases of Every faster and with full confidence.
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What Next Pathway's The Seven Phases of Every Migration covers
A successful Cloud migration requires a structured, phase-by-phase approach across discovery, code translation, validation, and cutover. Next Pathway's The Seven Phases of Every Migration gives your team a complete roadmap, built on the same automation Next Pathway uses to deliver enterprise migrations end to end.
Discovery & Assessment
Identify and inventory existing data, ETL processes, reports, and dependencies across the current environment. This phase establishes migration scope, uncovers technical complexity, and creates a baseline for planning and automation.
Migration Planning & Architecture
Define the target cloud architecture, migration sequencing, timelines, and resource requirements. Teams align on governance, security, testing strategies, and execution plans to reduce migration risk and avoid operational disruption.
Automated Code Translation & Modernization
Translate legacy SQL, ETL, and procedural code into cloud-native equivalents using automation. This phase accelerates migration timelines, improves consistency, and reduces the manual effort required to modernize enterprise workloads.
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 Migration Case Study
See how a British Asset Management Firm accelerated its migration from Azure Synapse and Azure Data Factory to Snowflake with automation, reducing complexity and modernizing its data platform.
What Industry Analysts Say
Rob Enderle
ENDERLE GROUP
Eric Kavanagh
THE BLOOR GROUP
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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