SDF is a build system for data that simplifies SQL development with local execution, workflows, and data governance features.

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Sdf is for data engineers and analytics engineers who build SQL-based data models and want to catch issues before deploying changes to a warehouse. It compiles SQL across dialects, checks models against available schema information, and can run SQL locally so developers can test and iterate without relying on warehouse execution for every change. Teams can use Sdf to organize and run transformation workflows, identify how tables and columns depend on one another, and review the effects of changes before they reach production. Its metadata and governance features help teams apply business rules and guardrails to data projects. Sdf may suit teams managing complex SQL transformations across data warehouses, especially when local development, impact analysis, and column-level lineage are important.

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