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Microsoft DP-700 Exam Syllabus Topics:

Topic	Details
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	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.
Topic 3	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.

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q46-Q51):

NEW QUESTION # 46
You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1. You perform the following actions:
* Connect Workspace1 to a Git repository and select the main branch.
* Create a new branch named feature! and modify Lakehouse1.
* Merge the changes from feature1 into the main branch.
You need to ensure that the changes are available in Workspace1. The solution must minimize changes to Workspace1 What should you do?

A. From Workspace1, select Source control, and then select Commit
B. Disconnect Workspace1 from the Git repository and reconnect Workspace1 to the main branch.
C. Switch Workspace1 to the feature1 branch and refresh the workspace.
D. From Workspace1, select Source control, and then select Updates

Answer: D

NEW QUESTION # 47
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.

A. Set the Retry setting of the Semantic model refresh activity to 2.
B. From the Schedule settings of Pipeline1, set the time zone to UTC.
C. From the Schedule settings of Notebook1, set the time zone to UTC.
D. Set the Retry setting of the Notebook activity to 2.
E. Place the Semantic model refresh activity after the Notebook activity and link the activities by using an On completion condition.
F. Place the Semantic model refresh activity after the Notebook activity and link the activities by using the On success condition.

Answer: B,D,F

NEW QUESTION # 48
DRAG DROP
You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiDat a. The following is a sample of the data in TaxiData.

You need to build two KQL queries. The solution must meet the following requirements:
One of the queries must partition RunningTotalAmount by VendorID.
The other query must create a column named FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
How should you complete each query? To answer, drag the appropriate values the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 49
You need to recommend a Fabric streaming solution that will use the sources shown in the following table.

The solution must minimize development effort.
What should you include in the recommendation for each source? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 50
You have a Fabric workspace that contains a large table named Table1. Table1 contains 2 billion rows.
You have a data source that generates a data file every 30 minutes The file contains only changes that occurred since the last file was generated.
You plan to deploy a data pipeline that will process each data file when it is generated and load the contents into Table1. You need to recommend which loading pattern to use for the following operations:
* Create new records.
* Delete existing records.
The solution must support the versioning of existing records.
What should you recommend for each operation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 51
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