DP-700 Free Practice Test

- (Topic 3)
You have a Fabric workspace that contains a warehouse named Warehouse1. Data is loaded daily into Warehouse1 by using data pipelines and stored procedures.
You discover that the daily data load takes longer than expected.
You need to monitor Warehouse1 to identify the names of users that are actively running queries.
Which view should you use?

1. A. sys.dm_exec_connections
2. B. sys.dm_exec_requests
3. C. queryinsights.long_running_queries
4. D. queryinsights.frequently_run_queries
5. E. sys.dm_exec_sessions

Correct Answer: E
sys.dm_exec_sessions provides real-time information about all active sessions, including the user, session ID, and status of the session. You can filter on session status to see users actively running queries.

HOTSPOT - (Topic 3)
You have an Azure Event Hubs data source that contains weather data.
You ingest the data from the data source by using an eventstream named Eventstream1. Eventstream1 uses a lakehouse as the destination.
You need to batch ingest only rows from the data source where the City attribute has a value of Kansas. The filter must be added before the destination. The solution must minimize development effort.
What should you use for the data processor and filtering? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Solution:


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

DRAG DROP - (Topic 3)
You have a Fabric eventhouse that contains a KQL database. The database contains a table named TaxiData. The following is a sample of the data in TaxiData.

You need to build two KQL queries. The solution must meet the following requirements: One of the queries must partition RunningTotalAmount by VendorID.
The other query must create a column named FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime partitioned by payment_type.
How should you complete each query? To answer, drag the appropriate values the correct targets. Each value 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.

Solution:
Partition the RunningTotalAmount by VendorID. - Row_cumsum
The Row_cumsum function computes the cumulative sum of a column while optionally restarting the accumulation based on a condition. In this case, it calculates the cumulative sum of total_amount for each VendorID, restarting when the VendorID changes (VendorID
!= prev(VendorID)).

Create a column FirstPickupDateTime that shows the first value of each hour from tpep_pickup_datetime, partitioned by payment_type - Row_window_session


Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: A

- (Topic 3)
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?

1. A. Yes
2. B. No

Correct Answer: B
An outer join will include unmatched rows from both tables, increasing the dataset size and processing time. It does not improve query performance.

- (Topic 3)
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 key vault URL and the name of a linked service.
Does this meet the goal?

1. A. Yes
2. B. No

Correct Answer: B