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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Maintain a data analytics solution | 25–30 | - Manage analytics development lifecycle
|
| Topic 2: Prepare data for analytics | 45–50 | - Implement data storage structures
|
| Topic 3: Implement and manage semantic models | 25–30 | - Design and build semantic models
|
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NEW QUESTION # 200
Your company has a finance department.
You have a Fabric tenant, an Azure Storage account named storagel, and a Microsoft Entra group named Groupl. Groupl contains the users in the finance department.
You need to create a new workspace named Workspacel in the tenant. The solution must meet the following requirements:
* Ensure that the finance department users can create and edit items in Workspace " !.
* Ensure that Workspacel can securely access storagel to read and write data.
* Ensure that you are the only admin of Workspacel.
* Minimize administrative effort.
You create Workspacel.
Which two actions should you perform next? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: B,C
Explanation:
Finance department users can create and edit items in Workspace1 #
The correct role is Contributor .
To minimize effort, assign this role to the Microsoft Entra group (Group1) instead of assigning it to each user individually.
So answer A is correct, not B .
Workspace1 can securely access storagel (Azure Storage) to read and write data # To connect a Fabric workspace to external resources securely, you use a Workspace identity (a managed identity for the workspace).
This allows Fabric items to authenticate to Azure Storage without embedding credentials.
So answer D is correct.
You are the only admin of Workspace1 #
By default, the workspace creator (you) is the admin. You do not need to explicitly reassign the admin role to yourself (so C is unnecessary).
Minimize administrative effort #
Assigning Contributor role to the group (A) is minimal effort compared to assigning it individually to each user (B).
A). Assign the Contributor role to Group1
D). Create a workspace identity
References:
Workspace roles in Microsoft Fabric
Workspace identity for secure data access
NEW QUESTION # 201
You have a Fabric tenant that contains two workspaces named Workspace1 and Workspace2.
Workspace1 is used as the development environment.
Workspace2 is used as the production environment.
Each environment uses a different storage account.
Workspace1 contains a Dataflow Gen2 named Dataflow1. The data source of Dataflow1 is a CSV file in blob storage.
You plan to implement a deployment pipeline to deploy items from Workspace1 to Workspace2.
You need to ensure that the data source references the correct location in the production environment.
What should you do?
Answer: D
Explanation:
Scenario:
Dev = Workspace1 with Dataflow Gen2 (source = blob storage CSV).
Prod = Workspace2, different storage account.
Need: ensure deployed dataflow points to the production storage location.
Analysis:
Data source rules: used to remap data sources between environments (e.g., blob storage dev # blob storage prod).
Parameter rules: used when the data source location is parameterized (for example, a parameter storing the file path or connection string).
Best practice: use parameters in the dataflow for connection strings, then apply parameter rules in deployment pipelines.
In this case, since the requirement is about ensuring the reference updates correctly, only parameter rules are needed (not data source rules).
NEW QUESTION # 202
You have a Fabric workspace named Workspace1 that contains a data flow named Dataflow1. Dataflow1 contains a query that returns the data shown in the following exhibit.
You need to transform the date columns into attribute-value pairs, where columns become rows.
You select the VendorlD column.
Which transformation should you select from the context menu of the VendorlD column?
Answer: D
Explanation:
The transformation you should select from the context menu of the VendorID column to transform the date columns into attribute-value pairs, where columns become rows, is Unpivot columns (B). This transformation will turn the selected columns into rows with two new columns, one for the attribute (the original column names) and one for the value (the data from the cells). References = Techniques for unpivoting columns are covered in the Power Query documentation, which explains how to use the transformation in data modeling.
NEW QUESTION # 203
You have Fabric tenant that contains four workspaces named Development, Test, QA, and Production. All the workspaces are in Premium Per User (PPU) license mode.
You plan to use a release pipeline to support the development lifecycle from Development to Production.
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:
Scenario Recap
Fabric tenant with workspaces: Development, Test, QA, Production.
All workspaces are already in Premium Per User (PPU) mode (which is required for deployment pipelines).
Task: Set up a release pipeline to move through Dev # Test # QA # Production.
Step 1: Create a deployment pipeline
The first step is always to create a new deployment pipeline in the Fabric/Power BI service. This establishes the structure for Dev # Test # Prod (and optionally QA).
Step 2: Create the QA stage
By default, pipelines have 3 stages (Dev, Test, Prod).
Since we need a QA stage in addition, we must explicitly add it as a stage to the pipeline.
Step 3: Assign workspaces
Once the pipeline structure is ready (with QA included), we assign each workspace to the corresponding stage:
Development # Development
Test # Test
QA # QA
Production # Production
Why Not the Other Actions?
Move each workspace to Pro license mode # Incorrect, because deployment pipelines require Premium capacity or PPU, and the workspaces already are in PPU mode.
Create a deployment rule # Deployment rules (e.g., parameter or data source rules) are optional for environment-specific changes, but not part of the initial required setup sequence.
References
Deployment pipelines overview
Assigning workspaces to deployment pipelines
NEW QUESTION # 204
You have a query in Power Query Editor that contains two columns named Order_Date and Shipping_Date.
You need to create a column that will calculate the number of days between Order_Date and Shipping_Date for each row.
Which Power Query function should you use?
Answer: A
Explanation:
Comprehensive Detailed Explanation
Requirement
We have two columns in Power Query Editor:
Order_Date
Shipping_Date
We need to calculate the number of days between the two dates.
Step 1: How date differences work in Power Query (M language)
Subtracting two date or datetime values in Power Query returns a duration value.
Example:
[Shipping_Date] - [Order_Date]
This produces a duration such as 3.00:00:00 (3 days).
Step 2: Converting duration into days
To get the number of days as an integer, we use Duration.Days().
Example:
Duration.Days([Shipping_Date] - [Order_Date])
This returns 3 if the shipping date is 3 days after the order date.
Step 3: Evaluate other options
A). Duration.From # Converts a value to a duration type but does not extract the number of days.
B). Date.AddDays # Adds days to a given date, not used for calculating the difference.
C). Duration.Days # Correct, extracts total days from a duration.
D). DateTime.LocalNow # Returns the current system datetime, unrelated to this requirement.
References
Duration.Days function (Power Query M)
Working with dates in Power Query
NEW QUESTION # 205
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