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Microsoft DP-700 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Implement and manage an analytics solution: This section of the exam measures the skills of Microsoft Data Analysts regarding configuring various workspace settings in Microsoft Fabric. It focuses on setting up Microsoft Fabric workspaces, including Spark and domain workspace configurations, as well as implementing lifecycle management and version control. One skill to be measured is creating deployment pipelines for analytics solutions.
Topic 2
  • Monitor and optimize an analytics solution: This section of the exam measures the skills of Data Analysts in monitoring various components of analytics solutions in Microsoft Fabric. It focuses on tracking data ingestion, transformation processes, and semantic model refreshes while configuring alerts for error resolution. One skill to be measured is identifying performance bottlenecks in analytics workflows.
Topic 3
  • Ingest and transform data: This section of the exam measures the skills of Data Engineers that cover designing and implementing data loading patterns. It emphasizes preparing data for loading into dimensional models, handling batch and streaming data ingestion, and transforming data using various methods. A skill to be measured is applying appropriate transformation techniques to ensure data quality.

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q105-Q110):

NEW QUESTION # 105
You have a Fabric workspace that contains a warehouse named Warehouse1. Warehouse1 contains a table named Customer. Customer contains the following data.

Answer:

Explanation:

Explanation:


NEW QUESTION # 106
HOTSPOT
You are building a data loading pattern for Fabric notebook workloads.
You have the following code segment:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 107
You have a Fabric workspace that contains a takehouse and a semantic model named Model1.
You use a notebook named Notebook1 to ingest and transform data from an external data source.
You need to execute Notebook1 as part of a data pipeline named Pipeline1. The process must meet the following requirements:
* Run daily at 07:00 AM UTC.
* Attempt to retry Notebook1 twice if the notebook fails.
* After Notebook1 executes successfully, refresh Model1.
Which three actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

Answer: A,C,F


NEW QUESTION # 108
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse2. A team of data analysts has Viewer role access to Workspace1. You create a table by running the following statement.

You need to ensure that the team can view only the first two characters and the last four characters of the Creditcard attribute.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 109
You have a Fabric workspace that contains an eventhouse named Eventhouse1.
In Eventhouse1, you plan to create a table named DeviceStreamData in a KQL database. The table will contain data based on the following sample.



You need to use a KQL query to develop the solution for Eventhouse 1.
Which three code segments should you run in sequence? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.
....

Answer:

Explanation:

Explanation:


NEW QUESTION # 110
......

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