A Fabric administrator needs to be notified when a specific data pipeline fails during the nightly ingestion of on-premises SQL Server data. The pipeline uses a gateway and has been failing intermittently due to gateway connectivity issues. The administrator wants to receive an email as soon as the pipeline fails, without having to manually check the Fabric portal. What should the administrator configure?

A data pipeline alert rule that triggers on pipeline failure and sends an email notification.

A Fabric activity log alert that triggers on any gateway connectivity event.

A Power BI report that shows pipeline run history and a manual email distribution list.

A scheduled refresh of the semantic model with a failure alert attached to the refresh.

What does the status 'Failed' in the semantic model refresh history indicate?

The refresh was canceled by the user

The refresh is still in progress

The refresh did not complete successfully, and the data may be out of date

The refresh completed but with warnings

What is the main benefit of configuring alerts for semantic model refreshes in Microsoft Fabric?

You are notified immediately if a refresh fails, allowing you to address data consistency issues quickly

Alerts increase the refresh speed

Alerts reduce the need for scheduled refreshes

Alerts automatically fix any refresh failures

A data engineering team uses Fabric notebooks to transform data. After a recent code change, the transformation runs successfully but produces unexpected row counts in the output table. The team needs to identify which step in the notebook caused the discrepancy. What should they do first?

Check the semantic model refresh history for the table that consumes the output.

Review the notebook run history and inspect the output of each cell in the failed run.

Use the Fabric monitoring hub to view the notebook's execution duration and status.

Enable detailed logging on the data pipeline that invokes the notebook.

Microsoft Certified:Fabric Data Engineer Associate

Domain 3Objective 1

Monitor Fabric Items DP-700 Practice Questions (Page 2)

Part of the Monitor and optimize an analytics solution domain, which accounts for 30–35% of the DP-700 exam. Microsoft does not publish an official question count, but from its 100-minute exam (~40–65 total, ~12–23 in this domain), expect 4–8 from this objective — we provide 18 practice questions to prepare you well beyond it. (estimate)

18questions here

4free pages

4concepts

30–35%of the exam

Questions 6–10

6application · medium
A Fabric administrator needs to be notified when a specific data pipeline fails during the nightly ingestion of on-premises SQL Server data. The pipeline uses a gateway and has been failing intermittently due to gateway connectivity issues. The administrator wants to receive an email as soon as the pipeline fails, without having to manually check the Fabric portal. What should the administrator configure?
Select an answer first
7foundation · easy
What does the status 'Failed' in the semantic model refresh history indicate?
Select an answer first
8foundation · easy
What is the main benefit of configuring alerts for semantic model refreshes in Microsoft Fabric?
Select an answer first
9application · medium
A data engineering team uses Fabric notebooks to transform data. After a recent code change, the transformation runs successfully but produces unexpected row counts in the output table. The team needs to identify which step in the notebook caused the discrepancy. What should they do first?
Select an answer first
10foundation · easy
In Microsoft Fabric, which feature allows you to see the execution details of a Dataflow Gen2, including the number of rows processed and the duration of each step?
Select an answer first

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Monitor Fabric Items DP-700 Practice Questions (Page 2)

Questions 6–10

What does the status 'Failed' in the semantic model refresh history indicate?

What is the main benefit of configuring alerts for semantic model refreshes in Microsoft Fabric?

A data engineering team uses Fabric notebooks to transform data. After a recent code change, the transformation runs successfully but produces unexpected row counts in the output table. The team needs to identify which step in the notebook caused the discrepancy. What should they do first?

In Microsoft Fabric, which feature allows you to see the execution details of a Dataflow Gen2, including the number of rows processed and the duration of each step?

Keep studying — Monitor and optimize an analytics solution