Microsoft DP-700 Certification Questions: Implementing Data Engineering Solutions Using Microsoft Fabric - PassExamDumps Last Updated Download

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Microsoft DP-700 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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.

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q79-Q84):

NEW QUESTION # 79
You have a Fabric workspace that contains a lakehouse named Lakehouse1.
In an external data source, you have data files that are 500 GB each. A new file is added every day.
You need to ingest the data into Lakehouse1 without applying any transformations. The solution must meet the following requirements Trigger the process when a new file is added.
Provide the highest throughput.
Which type of item should you use to ingest the data?

A. Event stream
B. Streaming dataset
C. Dataflow Gen2
D. Data pipeline

Answer: A

Explanation:
To ingest large files (500 GB each) from an external data source into Lakehouse1 with high throughput and to trigger the process when a new file is added, an Eventstream is the best solution.
An Eventstream in Fabric is designed for handling real-time data streams and can efficiently ingest large files as soon as they are added to an external source. It is optimized for high throughput and can be configured to trigger upon detecting new files, allowing for fast and continuous ingestion of data with minimal delay.

NEW QUESTION # 80
You have a Fabric workspace named Workspace1 that contains a notebook named Notebook1.
In Workspace1, you create a new notebook named Notebook2.
You need to ensure that you can attach Notebook2 to the same Apache Spark session as Notebook1.
What should you do?

A. Increase the number of executors.
B. Enable dynamic allocation for the Spark pool.
C. Change the runtime version.
D. Enable high concurrency for notebooks.

Answer: D

Explanation:
To ensure that Notebook2 can attach to the same Apache Spark session as Notebook1, you need to enable high concurrency for notebooks. High concurrency allows multiple notebooks to share a Spark session, enabling them to run within the same Spark context and thus share resources like cached data, session state, and compute capabilities. This is particularly useful when you need notebooks to run in sequence or together while leveraging shared resources.

NEW QUESTION # 81
HOTSPOT
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:

Explanation:

NEW QUESTION # 82
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?

A. From Monitoring hub, select the latest failed run of Pipeline1, and then view the output JSON.
B. From Monitoring hub, select the latest failed run of Pipeline1, and then view the input JSON.
C. From Real-time hub, select Fabric events, and then review the details of Microsoft. Fabric.ItemUpdateFailed.
D. From Real-time hub, select Fabric events, and then review the details of Microsoft.Fabric.ItemReadFailed.

Answer: B

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 # 83
You are building a data orchestration pattern by using a Fabric data pipeline named Dynamic Data Copy as shown in the exhibit. (Click the Exhibit tab.)

Dynamic Data Copy does NOT use parametrization.
You need to configure the ForEach activity to receive the list of tables to be copied.
How should you complete the pipeline expression? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

NEW QUESTION # 84
......

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Microsoft DP-700 Certification Questions: Implementing Data Engineering Solutions Using Microsoft Fabric - PassExamDumps Last Updated Download

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Microsoft DP-700 Exam Syllabus Topics:

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q79-Q84):

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