DP-700 Übungsfragen: Implementing Data Engineering Solutions Using Microsoft Fabric & DP-700 Dateien Prüfungsunterlagen

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Microsoft DP-700 Exam Syllabus Topics:

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

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DP-700 Trainingsmaterialien: Implementing Data Engineering Solutions Using Microsoft Fabric & DP-700 Lernmittel & Microsoft DP-700 Quiz

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric DP-700 Prüfungsfragen mit Lösungen (Q17-Q22):

17. Frage
You have a Fabric capacity that contains a workspace named Workspace1. Workspace1 contains a lakehouse named Lakehouse1, a data pipeline, a notebook, and several Microsoft Power BI reports.
A user named User1 wants to use SQL to analyze the data in Lakehouse1.
You need to configure access for User1. The solution must meet the following requirements:
Provide User1 with read access to the table data in Lakehouse1.
Prevent User1 from using Apache Spark to query the underlying files in Lakehouse1.
Prevent User1 from accessing other items in Workspace1.
What should you do?

Antwort: A

Begründung:
To meet the specified requirements for User1, the solution must ensure:
Read access to the table data in Lakehouse1: User1 needs permission to access the data within Lakehouse1. By sharing Lakehouse1 with User1 and selecting the Read all SQL endpoint data option, User1 will be able to query the data via SQL endpoints.
Prevent Apache Spark usage: By sharing the lakehouse directly and selecting the SQL endpoint data option, you specifically enable SQL-based access to the data, preventing User1 from using Apache Spark to query the data.
Prevent access to other items in Workspace1: Assigning User1 the Viewer role for Workspace1 ensures that User1 can only view the shared items (in this case, Lakehouse1), without accessing other resources such as notebooks, pipelines, or Power BI reports within Workspace1.
This approach provides the appropriate level of access while restricting User1 to only the required resources and preventing access to other workspace assets.


18. Frage
You have the development groups shown in the following table.

You have the projects shown in the following table.

You need to recommend which Fabric item to use based on each development group ' s skillset The solution must meet the project requirements and minimize development effort What should you recommend for each group? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Antwort:

Begründung:

Explanation:


19. Frage
You have an Azure SQL database named DB1.
In a Fabric workspace, you deploy an eventstream named EventStreamDBI to stream record changes from DB1 into a lakehouse.
You discover that events are NOT being propagated to EventStreamDBI.
You need to ensure that the events are propagated to EventStreamDBI.
What should you do?

Antwort: C


20. Frage
You have a Fabric workspace that contains an eventhouse and a KQL database named Database1. Database1 has the following:
A table named Table1
A table named Table2
An update policy named Policy1
Policy1 sends data from Table1 to Table2.
The following is a sample of the data in Table2.

Recently, the following actions were performed on Table1:
An additional element named temperature was added to the StreamData column.
The data type of the Timestamp column was changed to date.
The data type of the DeviceId column was changed to string.
You plan to load additional records to Table2.
Which two records will load from Table1 to Table2? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

Antwort: A,B

Begründung:
Changes to Table1 Structure:
StreamData column: An additional temperature element was added.
Timestamp column: Data type changed from datetime to date.
DeviceId column: Data type changed from guid to string.
Impact of Changes:
Only records that comply with Table2's structure will load.
Records that deviate from Table2's column data types or structure will be rejected.
Record B:
Timestamp: Matches Table2 (datetime format).
DeviceId: Matches Table2 (guid format).
StreamData: Contains only the index and eventid, which matches Table2.
Accepted because it fully matches Table2's structure and data types.
Record D:
Timestamp: Matches Table2 (datetime format).
DeviceId: Matches Table2 (guid format).
StreamData: Matches Table2's structure.
Accepted because it fully matches Table2's structure and data types.


21. Frage
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.

Antwort:

Begründung:

Explanation:


22. Frage
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