In the Databricks Lakehouse architecture, what is the recommended pattern for organizing data through successive stages of quality, from raw ingested data to aggregated business-ready data?

Question

Accepted Answer

B. Medallion architecture with bronze, silver, and gold layers. Databricks documentation recommends the medallion architecture, which organizes data into bronze (raw ingested data), silver (cleaned and validated data), and gold (aggregated, business-ready data) layers. Each layer progressively improves the quality and structure of data. Lambda and Kappa architectures are streaming system design patterns, not data quality layering patterns. Star schema is a dimensional data modeling technique, not a data quality progression model.

In the Databricks Lakehouse architecture, what is the recommended pattern for organizing data through successive stages of quality, from raw ingested data to aggregated business-ready data?

Related Questions

Discussion