Crucial Exams

Microsoft Fabric Data Engineer Associate DP-700 Practice Question

You need to design a nightly process that ingests 200 GB of semi-structured JSON sales files from an Azure Storage account into a Microsoft Fabric Lakehouse. The solution must land the files unchanged, instantly expose them to several other Lakehouses without duplication, and then run PySpark code that performs complex joins and writes a cleansed Delta table. Which two Fabric capabilities should you combine to meet these requirements?

  • Mount the storage account in the Lakehouse and schedule a KQL transformation.

  • Create a OneLake shortcut to the storage location and run a PySpark notebook.

  • Use a pipeline Copy activity followed by a dataflow Gen2.

  • Enable mirroring on the storage container and query the mirrored tables with T-SQL.

Microsoft Fabric Data Engineer Associate DP-700
Ingest and transform data
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