Microsoft Fabric Data Engineer Associate DP-700 Practice Question
A pipeline in Microsoft Fabric contains a Dataflow Gen2 that copies daily CSV files from Azure Data Lake Storage Gen2 into a lakehouse table. Last night the vendor added two new optional columns to the CSV schema, and the pipeline run failed with the following error:
"Column count mismatch between source and sink. Column 'NewField1' not found in the sink table."
You need to modify the dataflow so that future schema-drift changes in the source files do NOT cause the pipeline to fail and new columns are ignored until the lakehouse table is manually updated. Which change should you make?
Enable the Dynamic schema option on the Dataflow source and leave column mapping set to auto-detect.
Add an Alter Row transformation that routes rows with new columns to a reject sink.
Turn on Detect data types in the Dataflow sink settings and refresh the schema.
Set the Copy activity to use a staging folder in the lakehouse before the sink.
The failure occurs because the sink table's schema does not include the two new columns that appeared in the source files. In Dataflow Gen2, enabling the Dynamic schema option on the source tells the engine to load only the columns that exist in the sink schema and safely ignore any additional fields. This prevents future runs from failing when vendors add or remove columns. Adding an Alter Row transformation would still fail the copy if the schema does not match. Configuring a staging folder is unrelated to schema enforcement, and simply detecting data types on the sink does not address missing columns.
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Microsoft Fabric Data Engineer Associate DP-700
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