Which statement correctly contrasts a data warehouse with a data lake in an analytical architecture?
- AA data warehouse stores raw file-based data as-is, while a data lake enforces a relational SQL schema
- BA data warehouse uses a relational schema optimised for read queries, while a data lake holds raw file-based data Correct
- CA data warehouse is built for high-volume write transactions, while a data lake serves reporting queries only
- DA data warehouse holds only pre-aggregated measures, while a data lake holds the relational fact and dimension tables
Why A is wrong: This reverses the two stores: the lake collects large volumes of file-based data, while the warehouse is the relational, schema-based store.
Why B is correct: Correct. Data warehouses store data in a relational schema optimised for read operations to support reporting and visualisation, while data lakes collect large volumes of file-based data for analysis.
Why C is wrong: High-volume writes describe OLTP, not a warehouse; the warehouse is optimised for read queries that support reporting and visualisation.
Why D is wrong: Pre-aggregated measures belong to the OLAP semantic model, and fact and dimension tables sit in the warehouse rather than the lake.