DP-700 Monitor and Optimize an Analytics Solution Practice Question
You are monitoring a Dataflow Gen2 refresh that is failing intermittently. You need to identify if the failure is caused by a data type mismatch or a timeout from the source system. Which TWO actions will help you find the specific error details? (Choose two.)
⚠ Common exam trap
Candidates often look only at the 'Pipeline' logs. Dataflow Gen2 has its own distinct refresh history and error reporting mechanism that must be checked separately from the pipeline orchestration logs.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Check the 'Refresh history' in the Dataflow settings.
Dataflow Gen2 in Fabric provides multi-layered monitoring. The refresh history provides a high-level status, while the 'Request ID' can be used to trace the operation in more detail. For row-level errors, Dataflow Gen2 uses a specific mechanism to log transformation failures, allowing engineers to pinpoint exactly which record caused the process to fail.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Check the 'Refresh history' in the Dataflow settings.
Why this is correct
The Refresh History page provides a list of all past refresh attempts, their duration, and a summary of success or failure. For failed runs, it often provides an initial error message or a link to download a more detailed error log that contains the underlying Power Query exception.
- ✗
Enable 'Stage query' for all transformations.
Why it's wrong here
Staging queries is a performance optimization that allows Dataflow Gen2 to use the SQL compute engine for transformations. While it can improve speed, it does not provide additional logging or diagnostic information regarding data type mismatches or source connection timeouts during the refresh process.
- ✗
View the 'DataflowRefreshHistory' table in the Lakehouse.
Why it's wrong here
There is no default system table named 'DataflowRefreshHistory' automatically created in a user's Lakehouse. Monitoring information must be accessed through the Fabric portal's UI or by using the specific monitoring APIs provided by Microsoft Fabric for workspace and item management.
- ✓
Examine the 'On-premises data gateway' logs if applicable.
Why this is correct
If the Dataflow Gen2 is connecting to an on-premises source, the gateway logs are essential for diagnosing connection timeouts or network-level issues. These logs record the communication between Fabric and the local data source, providing clues that are not visible in the Fabric cloud portal.
- ✗
Use the 'Performance Analyzer' in Power BI Desktop.
Why it's wrong here
Performance Analyzer is a tool within Power BI Desktop used to measure the performance of report elements and DAX queries. It cannot be used to monitor or diagnose the refresh failures of a Dataflow Gen2 item that is running within the Fabric service environment.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This DP-700 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-700 exam.