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Microsoft DP-700 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Implement and manage an analytics solution30-35%- Orchestrate processes with Data Factory pipelines
- Configure and manage workspace settings and item access
- Implement security and governance
- Implement lifecycle management and source control for analytics assets
Topic 2: Monitor and optimize an analytics solution30-35%- Implement error handling in pipelines
- Optimize performance of data storage and queries
- Monitor Fabric items
Topic 3: Ingest and transform data30-35%- Design and implement loading patterns
- Optimize and manage Delta tables
- Ingest and transform data using eventstreams
- Transform data using Dataflows Gen2 and notebooks
- Ingest data using Data Factory pipelines and Dataflows Gen2

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q138-Q143):

NEW QUESTION # 138
You have a Fabric workspace named Workspace! that contains an Azure Data Factory pipeline named Pipeline1 You need to monitor the execution and activity status of Pipeline1 and automatically email an alert if the pipeline fails. The solution must minimize development and administrative effort.
What should you use to monitor Pipeline1, and what should you use to email the alert? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 139
You have a Fabric workspace named Workspace! that contains an Azure Data Factory pipeline named Pipeline1 You need to monitor the execution and activity status of Pipeline1 and automatically email an alert if the pipeline fails. The solution must minimize development and administrative effort.
What should you use to monitor Pipeline1, and what should you use to email the alert? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 140
You have a KQL database that contains two table named Stream and Reference. Stream contains streaming data in the following format.

Reference contains reference data in the following format.

Both tables contains millions of rows.
You have the following KQL queryset.

You need to reduce how long it takes to run KQL queryset.
Solution: You move the line 05 to line 02.
Does this meet the goal?

Answer: B


NEW QUESTION # 141
You have a Fabric workspace that contains an eventstream named EventStream1.
You discover that an EventStream1 transformation fails.
You need to find the following error information:
The error details, including the occurrence time
The total number of errors
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


NEW QUESTION # 142
You have a Fabric warehouse named DW1 that loads data by using a data pipeline named Pipeline1. Pipeline1 uses a Copy data activity with a dynamic SQL source. Pipeline1 is scheduled to run every 15 minutes.
You discover that Pipeline1 keeps failing.
You need to identify which SQL query was executed when the pipeline failed.
What should you do?

Answer: C

Explanation:
The input JSON contains the configuration details and parameters passed to the Copy data activity during execution, including the dynamically generated SQL query.
Viewing the input JSON for the failed pipeline run provides direct insight into what query was executed at the time of failure.


NEW QUESTION # 143
......

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