Microsoft Fabric Data Engineer Associate DP-700 Practice Question
You manage several Dataflow Gen2 objects in a Microsoft Fabric workspace. One dataflow's nightly refresh failed. Without leaving the Fabric portal or writing any code, you need to identify which table failed, how many rows each table processed, the duration of each table load, and the high-level error information for that run. Which Fabric capability should you open first to obtain this information?
Query the lakehouse _delta_log files with a Spark notebook to locate the failed commit.
Enable the Power BI Activity Log and export events to an Azure Storage account for analysis.
Open the dataflow's Refresh History pane in the workspace.
Configure Diagnostic Settings on the workspace to send Azure Monitor metrics to Log Analytics.
The Refresh History pane that is built into every Dataflow Gen2 provides entity-level monitoring details for each refresh. It shows the status of every table, the number of rows processed, the duration, and a summarized error message when a table fails. It is available directly in the workspace to anyone with Owner or Contributor permissions. The Power BI Activity Log records tenant-level events but does not include row counts or entity-level errors. Diagnostic settings in Azure Monitor capture service metrics, not detailed refresh data. Examining _delta_log files only reveals storage-level commits, not which table failed during the dataflow refresh.
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What is the Refresh History pane in Dataflow Gen2?
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Why can't the Power BI Activity Log help pinpoint table issues in a dataflow refresh?
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What are _delta_log files, and why are they insufficient for identifying table failures in Dataflow Gen2?
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Microsoft Fabric Data Engineer Associate DP-700
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