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Microsoft Implementing Analytics Solutions Using Microsoft Fabric Sample Questions (Q146-Q151):

NEW QUESTION # 146
You have a Fabric tenant that contains a Microsoft Power Bl report.
You are exploring a new semantic model.
You need to display the following column statistics:
* Count
* Average
* Null count
* Distinct count
* Standard deviation
Which Power Query function should you run?

Answer: C

Explanation:
The Table.Profile function in Power Query is used to generate column statistics such as count, average, null count, distinct count, and standard deviation. You can use this function as follows:
Invoke the Power Query Editor.
Apply the Table.Profile function to your table.
The result will be a table where each row represents a column from the original table, and each column in the result represents a different statistic such as those listed in the requirement.


NEW QUESTION # 147
You have a Microsoft Power Bl project that contains a semantic model. You plan to use Azure DevOps for version control.
You need to modify the .gitignore file to prevent the data values from the data sources from being pushed to the repository. Which file should you reference?

Answer: B

Explanation:
When using Power BI Project (.pbip) with Git integration:
The .pbip project separates model metadata (schema, measures, relationships, etc.) from actual data values.
The localSettings.json file stores machine-specific and environment-specific settings, including data source credentials and local configurations. These should not be checked into version control to avoid exposing sensitive information or environment-specific configs.
Other options:
unappliedChanges.json # tracks unsaved changes, not data values.
model.bim # defines the semantic model schema (measures, relationships, metadata) and must be included in version control.
cache.abf # stores Analysis Services cache data, not part of source control.
Therefore, the correct file to exclude is localSettings.json.
ference:
Power BI Projects and Git integration
localSettings.json in PBIP projects


NEW QUESTION # 148
You have a Fabric tenant that contains a complex semantic model. The model is based on a star schema and contains many tables, including a fact table named Sales.
You need to create a diagram of the model. The diagram must contain only the Sales table and related tables.
What should you use from Microsoft Power BI Desktop?

Answer: B

Explanation:
In the Model view, it is possible to analyze the semantic model and create new layouts.


NEW QUESTION # 149
Case Study 1 - Contoso
Overview
Contoso, Ltd. is a US-based health supplements company. Contoso has two divisions named Sales and Research. The Sales division contains two departments named Online Sales and Retail Sales. The Research division assigns internally developed product lines to individual teams of researchers and analysts.
Existing Environment
Identity Environment
Contoso has a Microsoft Entra tenant named contoso.com. The tenant contains two groups named ResearchReviewersGroup1 and ResearchReviewersGroup2.
Data Environment
Contoso has the following data environment:
- The Sales division uses a Microsoft Power BI Premium capacity.
- The semantic model of the Online Sales department includes a fact table named Orders that uses Import made. In the system of origin, the OrderID value represents the sequence in which orders are created.
- The Research department uses an on-premises, third-party data warehousing product.
- Fabric is enabled for contoso.com.
- An Azure Data Lake Storage Gen2 storage account named storage1 contains Research division data for a product line named Productline1. - The data is in the delta format.
- A Data Lake Storage Gen2 storage account named storage2 contains Research division data for a product line named Productline2. The data is in the CSV format.
Requirements
Planned Changes
Contoso plans to make the following changes:
- Enable support for Fabric in the Power BI Premium capacity used by the Sales division.
- Make all the data for the Sales division and the Research division available in Fabric.
- For the Research division, create two Fabric workspaces named Productline1ws and Productine2ws.
- In Productline1ws, create a lakehouse named Lakehouse1.
- In Lakehouse1, create a shortcut to storage1 named ResearchProduct.
Data Analytics Requirements
Contoso identifies the following data analytics requirements:
- All the workspaces for the Sales division and the Research division must support all Fabric experiences.
- The Research division workspaces must use a dedicated, on-demand capacity that has per- minute billing.
- The Research division workspaces must be grouped together logically to support OneLake data hub filtering based on the department name.
- For the Research division workspaces, the members of ResearchReviewersGroup1 must be able to read lakehouse and warehouse data and shortcuts by using SQL endpoints.
- For the Research division workspaces, the members of ResearchReviewersGroup2 must be able to read lakehouse data by using Lakehouse explorer.
- All the semantic models and reports for the Research division must use version control that supports branching.
Data Preparation Requirements
Contoso identifies the following data preparation requirements:
- The Research division data for Productline1 must be retrieved from Lakehouse1 by using Fabric notebooks.
- All the Research division data in the lakehouses must be presented as managed tables in Lakehouse explorer.
Semantic Model Requirements
Contoso identifies the following requirements for implementing and managing semantic models:
- The number of rows added to the Orders table during refreshes must be minimized.
- The semantic models in the Research division workspaces must use Direct Lake mode.
General Requirements
Contoso identifies the following high-level requirements that must be considered for all solutions:
- Follow the principle of least privilege when applicable.
- Minimize implementation and maintenance effort when possible.
You need to recommend which type of Fabric capacity SKU meets the data analytics requirements for the Research division.
What should you recommend?

Answer: A

Explanation:
The Research division workspaces must use a dedicated, on-demand capacity that has per- minute billing.


NEW QUESTION # 150
You have a Fabric workspace named Workspace1 that contains a dataflow named Dataflow1. Dataflow1 returns 500 rows of data.
You need to identify the min and max values for each column in the query results.
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: B,C,D

Explanation:
Scenario Recap
* You are working in Dataflow Gen2 inside a Fabric workspace.
* Dataflow1 returns 500 rows.
* You want to identify the minimum and maximum values for each column in the query results.
Key Concept: Column Profiling in Power Query (Fabric Dataflows)
In Power Query (used in Dataflows), profiling tools help you inspect and understand data. The following profiling features are available:
* Column quality # Shows % valid, % error, % empty values.
* Does not show min/max values.
* Column distribution # Shows distinct and unique value distribution (frequency).
* Does not show min/max values.
* Column profile # Provides statistics for each column including:
* Minimum value
* Maximum value
* Average, Standard deviation, Count, etc.
* This is the feature required here.
* Details pane # Displays the profiling results when profiling options (such as column profile) are enabled.
Correct Answer Breakdown
B). Show column profile in details pane
* Must be selected to display min/max, averages, and distribution in the details pane.
C). Enable details pane
* Required to actually display the profiling results. Without enabling the details pane, you cannot see column profiles.
E). Enable column profile
* Enables the calculation of statistics (min, max, avg, etc.) for each column.
These three together give you the ability to see min and max values.
Why the Other Options Are Incorrect
A). Show column quality details
* Shows only valid/empty/error statistics. No min/max.
D). Show column value distribution
* Displays distinct/unique values and counts but does not calculate min/max.
Summary
To identify min and max values per column in a Fabric Dataflow, you must:
* Enable the details pane
* Enable column profile
* Show column profile in details pane
Correct answers: B, C, E
References
* Data profiling tools in Power Query
* Column profiling options in Power Query
* Fabric Dataflows Gen2 overview


NEW QUESTION # 151
......

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