A customer asks whether adopting a lakehouse means abandoning SQL and BI tooling in favour of a file-based workflow. What is the correct response?
Select an answer to reveal the explanation.
Short Explanation
You don't have to abandon SQL or BI tooling. In a lakehouse, tables are queried with SQL through engines, and BI tools connect over standard interfaces just as they would to a warehouse.
Full Explanation
The correct response is the one saying no: tables are queried with SQL through engines, and BI tools connect over standard interfaces as they would to a warehouse. The lakehouse presents tables. Analysts write SQL against engines, and BI tools connect through standard interfaces, so the consumption experience closely resembles a warehouse. The architectural change is in how and where data is stored and governed, not in how it is consumed.
The option saying yes, lakehouse consumption is file-based and BI tools must read objects directly, is incorrect because file-based consumption is what open table formats and catalogs exist to eliminate. Direct object reads also bypass governance.
The option saying partly, SQL is supported for reads only and writes require a file-level API, is incorrect because SQL covers writes as well; inserts, updates, deletes, and merges are supported by the table formats.
The option saying yes for existing tools, though new tools can be written against the SQL interface, is incorrect because existing standards-based tools connect without modification. That compatibility is a deliberate design goal.
For the exam, keep the consumption story unchanged - SQL and standard interfaces - while the storage and governance story is what the lakehouse changes.