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| Section | Objectives |
|---|---|
| Get data into Microsoft Fabric | - Data ingestion and integration
|
| Implement analytics solutions | - Data warehousing and modeling
|
| Implement data engineering solutions | - Lakehouse architecture
|
| Manage and secure Microsoft Fabric | - Governance and administration
|
| Real-time analytics | - Streaming and event processing
|
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NEW QUESTION # 107
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 Fabric tenant that contains a lakehouse named Lakehousel. Lakehousel contains a Delta table named Customer.
When you query Customer, you discover that the query is slow to execute. You suspect that maintenance was NOT performed on the table.
You need to identify whether maintenance tasks were performed on Customer.
Solution: You run the following Spark SQL statement:
DESCRIBE DETAIL customer
Does this meet the goal?
Answer: B
NEW QUESTION # 108
You have a Fabric tenant that contains a warehouse named Warehouse!. Warehousel contains two schemas name schemal and schema2 and a table named schemal.city.
You need to make a copy of schemal.city in schema2. The solution must minimize the copying of data.
Which T-SQL statement should you run?
Answer: C
Explanation:
INSERT INTO ... SELECT and SELECT INTO both physically copy all rows, which is heavy and not minimal.
CREATE TABLE AS SELECT (CTAS) also copies the data.
CREATE TABLE ... AS CLONE OF creates a shallow clone in Fabric Warehouse, meaning it references the existing data without duplicating it, minimizing storage and copying.
Correct answer: B.
Reference: Clone tables in Fabric warehouse
NEW QUESTION # 109
You have a Fabric workspace named Workspace1.
You need to create a semantic model named Model1 and publish Model1 to Workspace1. The solution must meet the following requirements:
* Can revert to previous versions of Model1 as required.
* Identifies differences between saved versions of Model1.
* Uses Microsoft Power BI Desktop to publish to Workspace1.
* Can edit item definition files by using Microsoft Visual Studio Code.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,C
NEW QUESTION # 110
You have a Microsoft Power BI project that contains a file named definition.pbir. definition.pbir contains the following JSON.
Answer:
Explanation:
Explanation:
NEW QUESTION # 111
You have a Fabric tenant.
You are creating a Fabric Data Factory pipeline.
You have a stored procedure that returns the number of active customers and their average sales for the current month.
You need to add an activity that will execute the stored procedure in a warehouse. The returned values must be available to the downstream activities of the pipeline.
Which type of activity should you add?
Answer: A
Explanation:
In a Fabric Data Factory pipeline, to execute a stored procedure and make the returned values available for downstream activities, the Lookup activity is used. This activity can retrieve a dataset from a data store and pass it on for further processing. Here's how you would use the Lookup activity in this context:
* Add a Lookup activity to your pipeline.
* Configure the Lookup activity to use the stored procedure by providing the necessary SQL statement or stored procedure name.
* In the settings, specify that the activity should use the stored procedure mode.
* Once the stored procedure executes, the Lookup activity will capture the results and make them available in the pipeline's memory.
* Downstream activities can then reference the output of the Lookup activity.
References: The functionality and use of Lookup activity within Azure Data Factory is documented in Microsoft's official documentation for Azure Data Factory, under the section for pipeline activities.
NEW QUESTION # 112
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