Explain how to design a data warehouse with bronze, silver, and gold layers, and how to create dynamic views for user queries in such a warehouse.

In a modern data warehouse, the bronze layer stores raw, ingested data with minimal transformation. The silver layer cleanses, enriches, and aggregates data, applying business rules and schema enforcement. The gold layer contains curated, business‑ready tables optimized for analytics. To support dynamic views, you can create a metadata catalog (e.g., AWS Glue Data Catalog or Snowflake’s Information Schema) that records the lineage and schema of each layer. When a user requests a view, the system consults the catalog to determine which tables to join and which transformations to apply. You can generate the view on the fly using a templating engine that substitutes user‑specific filters or dimensions. For example, a user might request sales by region; the system builds a view that joins the silver sales table with the gold region dimension, applying any user‑defined filters. By keeping the underlying tables immutable and using parameterized views, you maintain consistency while allowing ad‑hoc analysis. This approach scales because the heavy lifting is done in the warehouse, and the view layer is lightweight and reusable.