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質問 # 145
You have a Fabric tenant.
You plan to create a data pipeline named Pipeline1. Pipeline1 will include two activities that will execute in sequence.
You need to ensure that a failure of the first activity will NOT block the second activity.
Which conditional path should you configure between the first activity and the second activity?
正解：C
質問 # 146
You need to recommend a solution to group the Research division workspaces.
What should you include in the recommendation? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Comprehensive Detailed Explanation
The requirement is to logically group the Research division workspaces and support filtering in the OneLake data hub .
Why Domain ?
Microsoft Fabric allows you to assign workspace domains (e.g., Finance, HR, Research).
This provides a logical grouping of workspaces within the organization.
Domains are the only supported way to enable filtering in OneLake data hub by department .
Capacity or tenant grouping would not allow filtering by department in OneLake.
Why OneLake data hub ?
The OneLake data hub is the centralized interface to browse and discover data assets across the organization.
With workspace domains configured, users can filter directly in the OneLake data hub by domain (e.g.,
"Research").
The Fabric Admin portal and Entra admin center are used for administration, not for workspace filtering in data discovery.
Correct Selection for the Hotspot
Grouping method: Domain
Tool: OneLake data hub
References
Workspace domains in Microsoft Fabric
Discover and filter data in OneLake data hub
Grouping method = Domain
Tool = OneLake data hub
質問 # 147
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 ensure that Contoso can use version control to meet the data analytics requirements and the general requirements.
What should you do?
正解：B
解説：
Currently, only Git in Azure Repos is supported.
https://learn.microsoft.com/en-us/fabric/cicd/git-integration/intro-to-git-integration#considerations- and-limitations
質問 # 148
You have a Microsoft Power BI project that contains a file named definition.pbir. definition.pbir contains the following JSON.
正解：
解説：
Explanation:
質問 # 149
You have a Fabric tenant that contains a semantic model. The model contains 15 tables.
You need to programmatically change each column that ends in the word Key to meet the following requirements:
* Hide the column.
* Set Nullable to False.
* Set Summarize By to None
* Set Available in MDX to False.
* Mark the column as a key column.
What should you use?
正解：D
解説：
Tabular Editor is an advanced tool for editing Tabular models outside of Power BI Desktop that allows you to script out changes and apply them across multiple columns or tables. To accomplish the task programmatically, you would:
Open the model in Tabular Editor.
Create an Advanced Script using C# to iterate over all tables and their respective columns.
Within the script, check if the column name ends with 'Key'.
For columns that meet the condition, set the properties accordingly: IsHidden = true, IsNullable = false, SummarizeBy = None, IsAvailableInMDX = false.
Additionally, mark the column as a key column.
Save the changes and deploy them back to the Fabric tenant.
質問 # 150
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