Migrate SQL Server to Snowflake with dbt and Altimate Code
Stored procedure logic in, validated dbt models out — with row count checks, schema diffs, and a migration dashboard stakeholders can actually trust.
OVERVIEW
Migrating SQL Server stored procedures to Snowflake and dbt is one of the highest-risk data projects a team can run. It's not just about translating syntax. It's about proving the output is identical.
This walkthrough covers the full migration lifecycle with Altimate Code: reading stored procedure business logic, converting it into dbt models structured across staging, silver, gold, and analytics layers, and validating every step of the way. Migration best practices are applied throughout to ensure output matches team standards and the target Snowflake architecture.
Validation runs at multiple levels: schema diff to catch structural mismatches, row count comparison between SQL Server and Snowflake, and column-level data diff to confirm migrated outputs match the original source exactly. The session ends with a migration validation dashboard showing status, results, model mappings, lineage, and key metrics — the kind of artifact that gives stakeholders actual confidence, not just an engineer's word that it worked.
WHAT YOU'LL LEARN
- →How to convert SQL Server stored procedure logic into structured dbt models
- →How to apply a medallion architecture (staging → silver → gold → analytics) during migration
- →How to validate migrations with schema diff, row count comparison, and column-level data diff
- →How to generate a migration validation dashboard for stakeholder sign-off
KEY POINTS
- Reads SQL Server stored procedure logic and converts it into layered dbt models
- Applies migration best practices and medallion layering throughout
- Validates with row count checks between SQL Server and Snowflake
- Runs schema diff and column-level data diff to confirm output matches the source
- Generates an interactive migration validation dashboard for stakeholder review
