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Question 66

Case study -

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

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.

What should you use to implement calculation groups for the Research division semantic models?

    Correct Answer: D

    Tabular Editor is the best choice for implementing calculation groups for semantic models. This tool has long supported the creation of calculation groups and is well-suited for minimizing implementation and maintenance effort. While other tools like Power BI Desktop have recently added features for creating calculation groups, Tabular Editor is more specialized and efficient for this task, adhering to the requirement of minimizing effort.

Discussion
obiiOption: D

The answer is D https://www.bing.com/videos/riverview/relatedvideo?q=how+to+implement+calculation+group+in+fabric&mid=DE305C502B1A6DA8AA03DE305C502B1A6DA8AA03&FORM=VIRE

MM_GG

seems the answer is really D https://powerbi.microsoft.com/en-us/blog/announcing-calculation-groups-for-direct-lake-datasets/

stilferxOption: D

IMHO, D (Tabular Editor) Requirements: The semantic models in the Research division workspaces must use Direct Lake mode. Considering Contoso's requirement to minimize implementation and maintenance effort (general requirement), Tabular Editor offers a more efficient way to define calculation groups compared to manually writing DAX code. Additionally, since calculation groups are part of the semantic model itself, they can be deployed and managed alongside the model, simplifying maintenance.

zerone72Option: D

Since a few moths ago you can create calculation group with a recent PowerBI Desktop version too. https://learn.microsoft.com/it-it/power-bi/transform-model/calculation-groups However, if I was to choose one only answer I'd go for Tabular Editor. You can create calculation group with Tabular editor since PowerBI desktop first version (years ago).

belhaOption: D

ANSWER IS D

b65eccaOption: D

I was studying with practice assessment on Microsoft Learn's own page. I came across to a similar question: "You have a Fabric workspace that contains a lakehouse named Lakehouse1. Lakehouse1 requires additional time intelligence calculations added to its semantic model. The model has XMLA read/write permissions enabled. You need to add a calculation group to the Lakehouse1 semantic model. What should you use?" The answer is Tabular Editor and explanation is as follows: Only Tabular Editor 2/3 can currently add calculation groups to a lakehouse semantic model. https://learn.microsoft.com/en-us/training/modules/create-calculation-groups/

EvincibleOption: D

Answer is D

EvincibleOption: B

The answer is B The power Bi service https://powerbi.microsoft.com/en-us/blog/model-explorer-and-calculation-groups-authoring-is-now-available-in-power-bi-service-including-direct-lake-semantic-models/

2dc6125Option: D

The safe answer is D: C DAX work only with explicit measures, power BI generate dax calculation so I'm not sure but safely D

4371883Option: D

Should be multiple choice, D is probably the safest option here.

neovermaOption: A

It should be A, using BI desktop... and if minimizing implementation was not mentioned then tabular editor.

neoverma

Although it can be implemented using service as well. if someone can share the reasoning, that would be great! https://powerbi.microsoft.com/en-us/blog/model-explorer-and-calculation-groups-authoring-is-now-available-in-power-bi-service-including-direct-lake-semantic-models/

gfors

So what is minimizing here? This can be done by Tabular editor, power bi desktop and now in the power bi service too according to that article. Both Tabular editor and Power bi desktop must do some extra things to publish it. Well in this question the answers are very close

napoleonxiv

The solution should support version control which presumably rules that out