Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric can feel demanding because it measures both knowledge recall and practical decision-making. With 144 DP-700 practice questions from Actual4dump, you can turn a broad syllabus into repeated, manageable review sessions.

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FAQs for Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Candidates

Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions:

Question 1

You are implementing the following data entities in a Fabric environment:
Entity1: Available in a lakehouse and contains data that will be used as a core organization entity Entity2: Available in a semantic model and contains data that meets organizational standards Entity3: Available in a Microsoft Power BI report and contains data that is ready for sharing and reuse Entity4: Available in a Power BI dashboard and contains approved data for executive-level decision making Your company requires that specific governance processes be implemented for the data.
You need to apply endorsement badges to the entities based on each entity's use case.
Which badge should you apply to each entity? To answer, drag the appropriate badges the correct entities.
Each badge 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.

Question 2

You have two Fabric workspaces named Workspace1 and Workspace2.
You have a Fabric deployment pipeline named deployPipeline1 that deploys items from Workspace1 to Workspace2. DeployPipeline1 contains all the items in Workspace1.
You recently modified the items in Workspaces1.
The workspaces currently contain the items shown in the following table.

Items in Workspace1 that have the same name as items in Workspace2 are currently paired.
You need to ensure that the items in Workspace1 overwrite the corresponding items in Workspace2. The solution must minimize effort.
What should you do?

A. Back up the items in Workspace2, and then run deployPipeline1.
B. Rename each item in Workspace2 to have the same name as the items in Workspace1.
C. Delete all the items in Workspace2, and then run deployPipeline1.
D. Run deployPipeline1 without modifying the items in Workspace2.

Question 3

You have a Fabric workspace that contains a lakehouse named Lakehousel.
You plan to create a data pipeline named Pipeline! to ingest data into Lakehousel. You will use a parameter named paraml to pass an external value into Pipeline1!. The paraml parameter has a data type of int You need to ensure that the pipeline expression returns param1 as an int value.
How should you specify the parameter value?

A. " @{pipeline().parameters.paraml} "
B. " @{pipeline().parameters.paraml}-
C. " @{pipeline().parameters.[paraml]} "
D. " @pipeline(). parameters. paraml "

Question 4

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

Question 5

You have a Fabric workspace named Workspace1 that contains three notebooks named notebook_01, notebook_02, and notebook_03.
You are building a new notebook in Workspace1 that will contain the following Directed Acyclic Graph (DAG) definition.

You need to modify the DAG definition to meet the following requirements:
* Ensure that notebook.01 and notebook_02 run in parallel.
* Ensure that notebook_02 only runs after the execution of notebook_03 is complete.
How should you modify the DAG definition?

A. Create a second DAG definition. Move notebook_03 and notebook_02 to the new DAG definition
B. Create two stages in the DAG definition. Add notebook_03 to the first stage. Add notebook_01 and notebook_02 to the second stage.
C. Move the notebook_03 declaration to the top of the DAG definition. Add a concurrency to notebook_02 and notebook_01.
D. Move the declaration of notebook 03 to the top of the DAG definition. Add a new stage that contains notebook 01 and notebook 02.

Solutions: