Post Title
Most data platforms don't fail because of missing tools. They fail because nobody trusts the numbers. The medallion architecture is a simple, proven way to fix that on Azure Databricks.
Bronze: land everything, change nothing
Ingest raw files and streams into Delta tables exactly as they arrive, with ingestion timestamps and source metadata. Auto Loader handles incremental file discovery, so new data is picked up without custom bookkeeping.
Silver: clean, conform, and deduplicate
This is where data types are enforced, bad records are quarantined, and entities from different systems are joined into a consistent model. Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) let you express these steps declaratively, with built-in data quality expectations.
Gold: model for the business
Aggregate silver data into tables shaped around real questions: revenue by region, customer lifetime value, inventory risk. These are the tables Power BI, Databricks SQL, and ML models should read from.
Govern it once with Unity Catalog
Catalogs, schemas, and fine-grained permissions sit on top of all three layers, and lineage shows exactly which gold metric came from which source file. That makes audits, impact analysis, and access reviews far easier.
Our takeaway
Start small. Pick one high-value domain, build bronze-to-gold end to end, prove the numbers match the business, then expand. A working slice beats a perfect blueprint.
