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Microsoft DP-700 Exam Syllabus Topics:

TopicDetails
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
  • 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
  • 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.

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q131-Q136):

NEW QUESTION # 131
You have a Fabric workspace named Workspace1 that contains a warehouse named DW1 and a data pipeline named Pipeline1.
You plan to add a user named User3 to Workspace1.
You need to ensure that User3 can perform the following actions:
View all the items in Workspace1.
Update the tables in DW1.
The solution must follow the principle of least privilege.
You already assigned the appropriate object-level permissions to DW1.
Which workspace role should you assign to User3?

Answer: A

Explanation:
To ensure User3 can view all items in Workspace1 and update the tables in DW1, the most appropriate workspace role to assign is the Contributor role. This role allows User3 to:
View all items in Workspace1: The Contributor role provides the ability to view all objects within the workspace, such as data pipelines, warehouses, and other resources.
Update the tables in DW1: The Contributor role allows User3 to modify or update resources within the workspace, including the tables in DW1, assuming that appropriate object-level permissions are set for the warehouse.
This role adheres to the principle of least privilege, as it provides the necessary permissions without granting broader administrative rights.


NEW QUESTION # 132
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?

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 # 133
You have a Fabric workspace named Workspace1 that contains a warehouse named Warehouse1.
You plan to deploy Warehouse1 to a new workspace named Workspace2.
As part of the deployment process, you need to verify whether Warehouse1 contains invalid references. The solution must minimize development effort.
What should you use?

Answer: A


NEW QUESTION # 134
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 # 135
You have a Fabric workspace that contains an eventstream named Eventstream1. Eventstream1 processes data from a thermal sensor by using event stream processing, and then stores the data in a lakehouse.
You need to modify Eventstream1 to include the standard deviation of the temperature.
Which transform operator should you include in the Eventstream1 logic?

Answer: C

Explanation:
To compute the standard deviation of the temperature from the thermal sensor data, you would use the Aggregate transform operator in Eventstream1. The Aggregate operator allows you to apply functions like sum, average, count, and statistical functions like standard deviation across a group of rows or events. This operator is ideal for operations that require summarizing or computing statistics over a dataset, such as calculating the standard deviation.


NEW QUESTION # 136
......

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