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| Section | Weight | Objectives |
|---|---|---|
| Model the Data | 25-30% | - Develop the data model
|
| Analyze the Data | 10-15% | - Work with metrics in Power BI
|
| Manage and Maintain Workspace Items | 10-15% | - Create and manage workspaces
|
| Prepare the Data | 10-15% | - Clean, transform, and load the data
|
| Visualize the Data | 25-30% | - Enhance reports for user experience
|
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NEW QUESTION # 25
You are creating a Power Bi model in Power BI Desktop
You need to create a calculated table named Numbers that will contain all the integers from -100 to 100. How should you complete the DAX calculation? To answer, select the appropriate options in the answer area.
NOTE Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 26
You have a query named All Sales that imports sales data into a Power BI model.
You plan to create a star schema by separating columns into separate queries and performing further transformations. The solution must meet the following requirements:
; Use All Sales as the source for three other queries named Sales Fact Product Dimension, and Customer Dimension.
; Minimize maintenance effort.
What should you do to create the Sales Fact query, and for which query should you clear Enable load? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
A star schema separates descriptive dimensions from event-level facts. Keeping the fact grain and relationship keys aligned supports correct aggregation and generally produces simpler, more efficient report queries. Use the selections preserved in the answer exhibit as the supported configuration. The relevant context is that the solution must meet the following requirements:; Use All Sales as the source for three other queries named Sales Fact Product Dimension, and Customer Dimension.; Minimize maintenance effort. Combining descriptive attributes and transactions at mixed grains makes keys and aggregation less predictable than a dimension-to-fact star design. This rationale is anchored to the PL-300 objective " Create fact tables and dimension tables " .
Microsoft Learn reference: https://learn.microsoft.com/en-us/power-bi/guidance/star-schema | PL-300 objective: " Create fact tables and dimension tables " | Study guide: https://learn.microsoft.com/en-us
/credentials/certifications/resources/study-guides/pl-300
NEW QUESTION # 27
You are creating a Microsoft Power BI data model that has the tables shown in the following table.
The Products table is related to the ProductCategory table through the ProductCategoryID column.
You need to ensure that you can analyze sales by product category.
How should you configure the relationships from Products to ProductCategory? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: One-to-many
Box 2: Both
For One-to-many relationships, the cross filter direction is always from the "one" side, and optionally from the "many" side (bi-directional).
Note:
Reference:
https://docs.microsoft.com/en-us/power-bi/transform-model/desktop-relationships-understand
NEW QUESTION # 28
DRAG DROP
You have a Microsoft Power Bl workspace.
You need to grant the user capabilities shown in the following table.
The solution must use the principle of least privilege.
Which user role should you assign to each user? To answer, drag the appropriate roles to the correct users. Each role 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.
Answer:
Explanation:
NEW QUESTION # 29
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.
From Power Query Editor, you profile the data shown in the following exhibit.
The IoT GUID and IoT ID columns are unique to each row in query.
You need to analyze IoT events by the hour and day of the year. The solution must improve dataset performance.
Solution: You change the IoT DateTime column to the Date data type.
Does this meet the goal?
Answer: A
Explanation:
Because changing the IoT DateTime column to the Date data type alone will not meet the goal of analyzing IoT events by the hour and day of the year in power query.
NEW QUESTION # 30
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