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Transformation components are used in transformation pipelines, which transform table data that already exists in your data warehouse—typically loaded there by an orchestration pipeline. These components are often analogs of SQL operations, allowing you to filter, join, aggregate, and reshape data without writing raw SQL.

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Common components

  • Table Input—reads data from an existing warehouse table into the pipeline.
  • Filter—keeps only rows matching defined criteria.
  • Aggregate—groups and summarizes data, for example summing a column per group.
  • Rank—ranks rows within partitions based on ordering criteria.
  • Rewrite Table—writes the transformed data permanently to a new or existing table.
AI components let you apply large language models to your warehouse data directly within a transformation pipeline:
Each component is exclusively applicable to one pipeline type—orchestration or transformation—and cannot be added to the other. To embed a transformation pipeline within an orchestration pipeline, use the Run Transformation component.