Microsoft Certified: Fabric Analytics Engineer AssociatePlan and implement data analytics solutions (10-15%)Medium
A company is migrating its existing data warehouse to Microsoft Fabric. The current data warehouse contains numerous fact and dimension tables, and they want to replicate the star schema design within their Fabric Lakehouse. They need an efficient way to manage and query these interrelated tables without physically duplicating data across different areas of the Lakehouse. Which Fabric feature should they leverage to achieve this while maintaining a single source of truth for the underlying data?
- AImporting all tables into a single Fabric Warehouse item.
- BManually copying and maintaining redundant copies of tables for different analytical needs.
- CUsing OneLake shortcuts to reference tables across different Lakehouse areas or even other Lakehouses.
- DCreating separate Lakehouses for each dimension and fact table.
Show answer & explanationAnswer & explanation
Correct answer: C. Using OneLake shortcuts to reference tables across different Lakehouse areas or even other Lakehouses.
OneLake shortcuts allow you to create virtual links to data located elsewhere in OneLake, including tables within the same or different Lakehouses, or even external ADLS Gen2 locations. This enables maintaining a single source of truth while providing flexible access and organization without data duplication.
Why the other options are wrong
- A. While a Fabric Warehouse can query Lakehouse tables, the question is about managing interrelated tables within the Lakehouse structure itself efficiently without duplication, which shortcuts facilitate.
- B. Manually copying redundant data is inefficient, leads to data inconsistencies, and increases storage costs, directly contradicting the goal of maintaining a single source of truth.
- D. Creating separate Lakehouses for each table would lead to management overhead and potential data silos, contrary to the goal of efficient management.
OneLake Shortcuts
OneLake shortcuts enable virtualized data access by creating references to data files or folders located elsewhere within OneLake or external cloud storage, promoting data reuse and avoiding duplication.
- Acts as a pointer, not a copy of data.
- Supports cross-Lakehouse and external data referencing.
- Facilitates logical data organization and sharing.
Memory trick: Shortcuts link, don't duplicate, for a single data state!