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 refresh the Orders table of the Online Sales department. The solution must meet the semantic model requirements.
What should you include in the solution?

You have a Fabric workspace named Workspace1 that contains a lakehouse named Lakehouse1 and a user named User1.
You need to ensure that User1 can read all the data in Lakehouse1. The solution must follow the principle of least privilege.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Drag and Drop Question
You have a Fabric tenant that contains a semantic model. The model contains data about retail stores.
You need to write a DAX query that will be executed by using the XMLA endpoint. The query must return a table of stores that have opened since December 1, 2023.
How should you complete the DAX expression? To answer, drag the appropriate values to the correct targets. Each value 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.

You have a Fabric workspace named Workspace1 that is assigned to a newly created Fabric capacity named Capacity1.
You create a semantic model named Model1 and deploy Model1 to Workspace1.
You need to publish changes to Model1 directly from Tabular Editor.
What should you do?

You have a Fabric workspace named Workspace1.
You need to create a semantic model named Model1 and publish Model1 to Workspace1. The solution must meet the following requirements:
- Can revert to previous versions of Model1 as required.
- Identifies differences between saved versions of Model1.
- Uses Microsoft Power Bl=I Desktop to publish to Workspace1.
- Can edit item definition files by using Microsoft Visual Studio Code.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.