Crucial Exams

Microsoft Fabric Data Engineer Associate DP-700 Practice Question

You are building a Lakehouse in Microsoft Fabric. A pipeline must ingest 200 GB of historical orders from Azure SQL Database once and then load only rows that changed since the last run each night. The pipeline triggers a Spark notebook that writes data to a Delta table in the Bronze layer. Which approach should you implement in the notebook to meet these requirements?

  • Enable Auto Optimize and Auto Compaction on the Delta table without additional logic; Spark will automatically detect and merge changes.

  • Use a Delta Lake MERGE INTO operation keyed on a persisted watermark column to upsert nightly changes.

  • Configure the pipeline to always overwrite the Delta table using COPY INTO with FILEFORMAT = PARQUET and a forced path option.

  • Issue a TRUNCATE TABLE statement on the Delta table followed by a full INSERT of all source rows each night.

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