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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q50-Q55):

NEW QUESTION # 50
You have a Fabric workspace named Workspace1 that contains a data pipeline named Pipeline1 and a lakehouse named Lakehouse1.
You have a deployment pipeline named deployPipeline1 that deploys Workspace1 to Workspace2.
You restructure Workspace1 by adding a folder named Folder1 and moving Pipeline1 to Folder1.
You use deployPipeline1 to deploy Workspace1 to Workspace2.
What occurs to Workspace2?

A. Folder1 is created, and Pipeline1 and Lakehouse1 move to Folder1.
B. Only Folder1 is created and Pipeline1 moves to Folder1.
C. Folder1 is created, Pipeline1 moves to Folder1, and Lakehouse1 is deployed.
D. Only Pipeline1 and Lakehouse1 are deployed.

Answer: C

Explanation:
When you restructure Workspace1 by adding a new folder (Folder1) and moving Pipeline1 into it, deployPipeline1 will deploy the entire structure of Workspace1 to Workspace2, preserving the changes made in Workspace1. This includes:
Folder1 will be created in Workspace2, mirroring the structure in Workspace1.
Pipeline1 will be moved into Folder1 in Workspace2, maintaining the same folder structure.
Lakehouse1 will be deployed to Workspace2 as it exists in Workspace1.

NEW QUESTION # 51
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?

A. Aggregate
B. Group by
C. Expand
D. Union

Answer: A

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 # 52
HOTSPOT
You are processing streaming data from an external data provider.
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.

Answer:

Explanation:

Explanation:

Litware from New York will be displayed at the top of the result set - Yes The data is sorted first by Location in descending order and then by UnitsSold in descending order. Since
"New York" is alphabetically the last Location, it will appear first in the result set. Within "New York", Litware has the highest UnitsSold (1000), so it will be displayed at the top.
Fabrikam in Seattle will have value = 2 in the Rank column - No
The row_rank_dense function assigns dense ranks based on UnitsSold within each location. In "Seattle":
Contoso has UnitsSold = 300 # Rank 1
Litware has UnitsSold = 100 # Rank 2
Fabrikam also has UnitsSold = 100, so it shares the same rank (2) as Litware.
Litware in San Francisco will have the same value in the Rank column as Litware in New York - No The rank is calculated separately for each location. In "San Francisco":
Both Relecloud and Litware have UnitsSold = 500, so they share the same rank (1).
In "New York", Litware has the highest UnitsSold = 1000 # Rank 1.
Since ranks are calculated independently for each location, Litware in San Francisco does not share the same rank as Litware in New York.

NEW QUESTION # 53
You have an Azure key vault named KeyVaultl that contains secrets.
You have a Fabric workspace named Workspace-!. Workspace! contains a notebook named Notebookl that performs the following tasks:
* Loads stage data to the target tables in a lakehouse
* Triggers the refresh of a semantic model
You plan to add functionality to Notebookl that will use the Fabric API to monitor the semantic model refreshes. You need to retrieve the registered application ID and secret from KeyVaultl to generate the authentication token.
Solution: You use the following code segment:
Use notebookutils.credentials.getSecret and specify the key vault URL and key vault secret. Does this meet the goal?

A. Yes
B. No

Answer: A

NEW QUESTION # 54
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. Enable dynamic allocation for the Spark pool.
B. Change the runtime version.
C. Increase the number of executors.
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 # 55
......

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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q50-Q55):

DP-700 real exam dumps: Implementing Data Engineering Solutions Using Microsoft Fabric & DP-700 free practice exam