migrating-sql-to-dbt

To convert SQL to dbt models, this Skill parses stored procedures, views, and raw SQL files, then guides you through structuring them into modular staging, intermediate, and mart layers. It automates checks for existing sources to ensure data consistency.

The best way to structure a SQL to dbt migration is by using a layered approach. This Skill sequentially builds and validates staging, intermediate, and mart layers, ensuring your data pipeline transitions successfully from legacy SQL transformations to dbt's model-driven architecture.

Yes, you need dbt installed to automate SQL database migration. The Skill requires dbt and SQL parsing capabilities to convert legacy SQL files into modular dbt models and validate the resulting data pipeline layers.

Yes, you can migrate legacy SQL views directly into dbt staging and marts. The Skill supports converting existing SQL views and raw files into dbt models, automatically checking for existing models and sources to reduce manual setup effort.

Converting SQL stored procedures to dbt requires a layered approach to ensure data consistency and modularity. By separating logic into staging, intermediate, and mart layers, the Skill validates each step sequentially, preventing pipeline failures during migration.

A limitation of automating SQL to dbt conversion is that it depends on SQL parsing capabilities and requires existing dbt infrastructure. Complex stored procedures may need manual adjustments to fit the staging, intermediate, and mart layer structure properly.