What data storage solution located in a Fabric workspace supports access via T-SQL or Python and can store unstructured or semi-structured data?

• A. Data lake
• B. Data warehouse
• C. Datamart
• D. Lakehouse

Answer: (D)

Access methods like T-SQL and Python alongside the ability to store unstructured or semi-structured data point to a lakehouse. A lakehouse combines the flexible storage of a data lake with the governance, performance, and schema features of a data warehouse, so you can keep raw or semi-structured data in one place and query it with SQL (T-SQL) or analyze it from Python. In Fabric, this unified storage model lets analysts run familiar SQL queries and data scientists work directly in Python on the same data, covering both workloads efficiently. By contrast, a data lake focuses on raw files without centralized SQL querying, a data warehouse centers on highly structured data optimized for SQL, and a datamart is a smaller, subject-area subset of a warehouse—none of these inherently pair unstructured data storage with both SQL and Python access in a single, unified way.