DP-700 Exam Torrent - Implementing Data Engineering Solutions Using Microsoft Fabric Prep Torrent & DP-700 Test Braindumps
DP-700 Exam Torrent - Implementing Data Engineering Solutions Using Microsoft Fabric Prep Torrent & DP-700 Test Braindumps
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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q31-Q36):
NEW QUESTION # 31
You have five Fabric workspaces.
You are monitoring the execution of items by using Monitoring hub.
You need to identify in which workspace a specific item runs.
Which column should you view in Monitoring hub?
- A. Capacity
- B. Job type
- C. Activity name
- D. Location
- E. Item type
- F. Submitter
- G. Start time
Answer: D
Explanation:
To identify in which workspace a specific item runs in Monitoring hub, you should view the Location column. This column indicates the workspace where the item is executed. Since you have multiple workspaces and need to track the execution of items across them, the Location column will show you the exact workspace associated with each item or job execution.
NEW QUESTION # 32
You have a Fabric workspace that contains a warehouse named Warehouse1.
You have an on-premises Microsoft SQL Server database named Database1 that is accessed by using an on-premises data gateway.
You need to copy data from Database1 to Warehouse1.
Which item should you use?
- A. an Apache Spark job definition
- B. a data pipeline
- C. an eventstream
- D. a Dataflow Gen1 dataflow
Answer: B
Explanation:
To copy data from an on-premises Microsoft SQL Server database (Database1) to a warehouse (Warehouse1) in Fabric, a data pipeline is the most appropriate tool. A data pipeline in Fabric is designed to move data between various data sources and destinations, including on-premises databases like SQL Server, and cloud-based storage like Fabric warehouses. The data pipeline can handle the connection through an on-premises data gateway, which is required to access on-premises data. This solution facilitates the orchestration of data movement and transformations if needed.
NEW QUESTION # 33
You have a Fabric workspace that contains two lakehouses named Lakehouse1 and Lakehouse2. Lakehouse1 contains staging data in a Delta table named Orderlines. Lakehouse2 contains a Type 2 slowly changing dimension (SCD) dimension table named Dim_Customer.
You need to build a query that will combine data from Orderlines and Dim_Customer to create a new fact table named Fact_Orders. The new table must meet the following requirements:
Enable the analysis of customer orders based on historical attributes.
Enable the analysis of customer orders based on the current attributes.
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:
NEW QUESTION # 34
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. Yes
- B. No
Answer: B
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 # 35
You have a Fabric workspace that contains a semantic model named Model1.
You need to dynamically execute and monitor the refresh progress of Model1.
What should you use?
- A. dynamic management views in Microsoft SQL Server Management Studio
- B. dynamic management views in Azure Data Studio
- C. Monitoring hub
- D. a semantic link in a notebook
Answer: D
Explanation:
Semantic models in Microsoft Fabric are part of Power BI datasets and require refreshes to stay updated with the latest data.
Dynamically executing and monitoring the refresh progress requires a tool or approach that integrates with Fabric's capabilities for semantic models.
NEW QUESTION # 36
......
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