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?
Correct Answer:A
- (Topic 3)
You are developing a data pipeline named Pipeline1.
You need to add a Copy data activity that will copy data from a Snowflake data source to a Fabric warehouse.
What should you configure?
Correct Answer:C
When using the Copy data activity in a data pipeline to move data from Snowflake to a Fabric warehouse, the process often involves intermediate staging to handle data efficiently, especially for large datasets or cross-cloud data transfers.
Staging involves temporarily storing data in an intermediate location (e.g., Blob storage or Azure Data Lake) before loading it into the target destination.
For cross-cloud data transfers (e.g., from Snowflake to Fabric), enabling staging ensures data is processed and stored temporarily in an efficient format for transfer.
Staging is especially useful when dealing with large datasets, ensuring the process is optimized and avoids memory limitations.
- (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 project to extend.
Does this meet the goal?
Correct Answer:B
Using extend retains all columns in the table, potentially increasing the size of the output unnecessarily. project is more efficient because it selects only the required columns.
- (Topic 2)
What should you do to optimize the query experience for the business users?
Correct Answer:B
HOTSPOT - (Topic 3)
You have a Fabric workspace.
You are debugging a statement and discover the following issues: Sometimes, the statement fails to return all the expected rows.
The PurchaseDate output column is NOT in the expected format of mmm dd, yy.
You need to resolve the issues. The solution must ensure that the data types of the results are retained. The results can contain blank cells.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Solution:
Does this meet the goal?
Correct Answer:A