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NEW QUESTION # 167
You create a semantic model by using Microsoft Power Bl Desktop. The model contains one security role named SalesRegionManager and the following tables:
* Sales
* SalesRegion
* Sales Ad dress
You need to modify the model to ensure that users assigned the SalesRegionManager role cannot see a column named Address in Sales Address.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
To ensure that users assigned the SalesRegionManager role cannot see the Address column in the SalesAddress table, follow these steps in sequence:
* Open the model in Tabular Editor.
* Select the Address column in SalesAddress.
* Set Object Level Security to None for SalesRegionManager.
NEW QUESTION # 168
You have a Fabric tenant.
You plan to create a Fabric notebook that will use Spark DataFrames to generate Microsoft Power Bl visuals.
You run the following code.
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The code embeds an existing Power BI report. - No
The code creates a Power BI report. - Yes
The code displays a summary of the DataFrame. - Yes
The code provided seems to be a snippet from a SQL query or script which is neither creating nor embedding a Power BI report directly. It appears to be setting up a DataFrame for use within a larger context, potentially for visualization in Power BI, but the code itself does not perform the creation or embedding of a report.
Instead, it ' s likely part of a data processing step that summarizes data.
References =
Introduction to DataFrames - Spark SQL
Power BI and Azure Databricks
NEW QUESTION # 169
You have a Microsoft Fabric tenant that contains a dataflow.
You are exploring a new semantic model.
From Power Query, you need to view column information as shown in the following exhibit.
Which three Data view options should you select? Each correct answer presents part of the solution. NOTE:
Each correct answer is worth one point.
Answer: A,B,D
Explanation:
To view column information like the one shown in the exhibit in Power Query, you need to select the options that enable profiling and display quality and distribution details. These are: A. Enable column profile - This option turns on profiling for each column, showing statistics such as distinct and unique values. B. Show column quality details - It displays the column quality bar on top of each column showing the percentage of valid, error, and empty values. E. Show column value distribution - It enables the histogram display of value distribution for each column, which visualizes how often each value occurs.
References: These features and their descriptions are typically found in the Power Query documentation, under the section for data profiling and quality features.
NEW QUESTION # 170
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 semantic model named Model1.
You discover that the following query performs slowly against Model1.
You need to reduce the execution time of the query.
Solution: You replace line 4 by using the following code:
Does this meet the goal?
Answer: B
Explanation:
The suggested replacement does not improve performance. COUNTROWS( ' Order Item ' ) < 0 is always false (row counts cannot be negative), so the NOT will always evaluate to true. This means the filter condition becomes non-selective and would return all customers, not just those with orders. Therefore, it does not meet the optimization goal.
NEW QUESTION # 171
You are analyzing customer purchases in a Fabric notebook by using PySpanc You have the following DataFrames:
You need to join the DataFrames on the customer_id column. The solution must minimize data shuffling. You write the following code.
Which code should you run to populate the results DataFrame?
Answer: B
Explanation:
The correct code to populate the results DataFrame with minimal data shuffling is Option A.
Using the broadcast function in PySpark is a way to minimize data movement by broadcasting the smaller DataFrame ( customers) to each node in the cluster.
This is ideal when one DataFrame is much smaller than the other, as in this case with customers.
References = You can refer to the official Apache Spark documentation for more details on joins and the broadcast hint.
NEW QUESTION # 172
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