Case Study 1 – Contoso, Ltd.
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.
