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You have a Fabric workspace named Workspacel that contains the following items:
* A Microsoft Power Bl report named Reportl
* A Power Bl dashboard named Dashboardl
* A semantic model named Modell
* A lakehouse name Lakehouse1
Your company requires that specific governance processes be implemented for the items. Which items can you endorse in Fabric?
A. Report1 and Dashboard1 only
B. Model1, Report1, and Dashboard1 only
C. Lakehouse1, Model1, and Report1 only
D. Lakehouse1, Modell, Report1 and Dashboard1
E. Lakehouse1, Modell, and Dashboard1 only
Answer: D
NEW QUESTION # 51
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a KQL database that contains two tables named Stream and Reference. Stream contains streaming data in the following format.
Reference contains reference data in the following format.
Both tables contain millions of rows.
You have the following KQL queryset.
You need to reduce how long it takes to run the KQL queryset.
Solution: You change the join type to kind=outer.
Does this meet the goal?
A. No
B. Yes
Answer: A
Explanation:
An outer join will include unmatched rows from both tables, increasing the dataset size and processing time.
It does not improve query performance.
NEW QUESTION # 52
You need to ensure that the data engineers are notified if any step in populating the lakehouses fails. The solution must meet the technical requirements and minimize development effort.
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 # 53
You have a Fabric workspace that contains a lakehouse named Lakehousel. Lakehousel contains a table named Status_Target that has the following columns:
* Key
* Status
* LastModified
The data source contains a table named Status.Source that has the same columns as Status_Target. Status.
Source is used to populate Status_Target. In a notebook name Notebook!, you load Status_Source to a DataFrame named sourceDF and Status_Target to a DataFrame named targetDF. You need to implement an incremental loading pattern by using Notebook-!. The solution must meet the following requirements:
* For all the matching records that have the same value of key, update the value of LastModified in Status_Target to the value of LastModified in Status_Source.
* Insert all the records that exist in Status_Source that do NOT exist in Status_Target.
* Set the value of Status in Status_Target to inactive for all the records that were last modified more than seven days ago and that do NOT exist in Status.Source.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation:
NEW QUESTION # 54
You need to schedule the population of the medallion layers to meet the technical requirements.
What should you do?
A. Schedule multiple data pipelines.
B. Schedule a data pipeline that calls other data pipelines.
C. Schedule a notebook.
D. Schedule an Apache Spark job.
Answer: B
NEW QUESTION # 55
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