Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You manage a Microsoft Fabric workspace that receives daily CSV files into a lakehouse bronze folder. The business wants a reusable transformation that non-developer analysts can build in the Power BI service without writing code. The solution must join the files, filter rows, create aggregates, and write the results to a dimension table in the same lakehouse. Which Fabric component should you use to build the transformation?
Create a Dataflow Gen2 that loads its output to the lakehouse table.
Implement a T-SQL stored procedure in a Fabric warehouse and call it from a pipeline.
Write a KQL query in a Real-Time Analytics database and materialize the results.
Develop a Spark notebook with PySpark transformations and schedule it in a pipeline.
Dataflow Gen2 uses the web-based Power Query editor, enabling analysts to create transformations without writing code and to output the results directly to a lakehouse table. Spark notebooks require PySpark skills, KQL targets Real-Time Analytics rather than scheduled batch processing into lakehouses, and T-SQL stored procedures require writing SQL code.
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Microsoft Fabric Data Engineer Associate DP-700
Ingest and transform data
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