Data Transformation platforms model raw data in the warehouse into clean, documented, tested analytical tables through code-defined workflows (SQL with templating, or Python). Core capabilities include incremental and full-refresh model materialization, unit-level tests and assertions, auto-generated lineage graphs, documentation generation, environment management (dev/staging/prod), CI/CD integration, and column-level impact analysis. The category defines the modern analytics engineering role and has become foundational to the warehouse-centric data stack. Leading vendors include dbt (Fivetran), SQLMesh, Coalesce, Dataform (Google), and Matillion on the transformation side.