gold-layer-design

Design a Gold layer schema by defining grains, dimensions, facts, and relationships, then generate ERDs, YAML schemas, and documentation for Databricks Delta Lake. This process applies standard table properties and dimensional modeling best practices.

Dimensional modeling for a Gold layer involves structuring data into fact and dimension tables to optimize analytical queries. It defines grains and relationships to ensure the schema delivers accurate, business-ready reporting.

Generate ERDs and YAML schemas by ingesting a source schema CSV file to guide the dimensional design. The process maps source tables to target Gold layer structures, producing YAML schemas that drive downstream table creation.

Yes, Databricks Delta Lake table properties are applied during the Gold layer design process. The workflow generates comprehensive business documentation, including ERDs, onboarding guides, and source table mappings alongside the schemas.

Applying naming and tagging standards is required before designing Gold layer schemas to ensure consistent metadata. These standards integrate with the dimensional modeling process to validate design and prepare for stakeholder review.

The best way to document dimensional models is to orchestrate the Gold layer design end-to-end, producing ERDs, business onboarding guides, and source table mappings. This ensures comprehensive documentation from initial intake to final validation.