Microsoft Fabric Data Engineer Associate DP-700 Practice Question

You must transform 200 GB of semi-structured logs in OneLake. Engineers need to use Python libraries like pandas and scikit-learn for feature engineering and visual analysis, then write the result to a Delta Lake table. The code should support iterative development and be runnable on a scheduled Fabric pipeline. Which Fabric transformation option best meets the requirements?

  • Dataflow Gen2

  • T-SQL stored procedure in a Fabric warehouse

  • Spark notebook

  • KQL database update policy

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