Microsoft Fabric Data Engineer Associate DP-700 Practice Question
Your company already lands sensor readings in Delta Lake tables inside an existing Fabric Lakehouse. A new project must run ad-hoc KQL queries over the latest readings with sub-second latency, but the compliance team insists that no additional copies of the data are created. In Real-Time Intelligence, which storage option should you choose for the KQL database that will power the queries?
Export the Delta tables to Azure Blob Storage and re-ingest the files into a new native KQL database.
Set up mirroring for the Lakehouse so that the Delta tables are replicated into Real-Time Intelligence.
Ingest the data into a native KQL database table by connecting the Lakehouse as a source.
Create a shortcut in the KQL database that points to the Lakehouse Delta tables.
Shortcuts let a KQL database in Real-Time Intelligence reference data that already resides in OneLake or a Fabric Lakehouse without copying the files. Because the data remains in its original Delta format, no regulatory-sensitive duplicates are created yet the database can still deliver low-latency, sub-second query performance. Native ingestion or mirroring would both create additional physical copies, and exporting then re-ingesting the data duplicates it again while adding unnecessary complexity.
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Microsoft Fabric Data Engineer Associate DP-700
Ingest and transform data
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