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Requirement Analysis

Sales table → Users should only see sales data for their own region .

This requires filtering rows based on a condition (e.g., Region = User’s Region).

The correct feature: Row-level security (RLS) .

Employees table → Restrict access to Personally Identifiable Information (PII) while allowing access to non-sensitive columns.

This requires restricting access to specific columns (such as SSN, phone, address, etc.), but leaving others visible.

The correct feature: Column-level security .

Maintain access to unrestricted data for all users → Both RLS and column-level security allow users to continue accessing non-restricted data.

Why Other Options Are Not Correct

Item permissions : Control access at the object level (e.g., table or report), not at the row or column level. Too coarse for this requirement.

Workspace permissions : Apply at the workspace level, not suitable for table-level data filtering.

Completed Answer

Employees → Column-level security

Sales → Row-level security (RLS)

References

Row-level security in Microsoft Fabric

Column-level security in Microsoft Fabric

The relationship between OrderItem and Product must be based on: Both the CompanyID and the ProductID columns

The Company entity must be: Denormalized into the Customer and Product entities

In a dimensional model, the relationships are typically based on foreign key constraints between the fact table (OrderItem) and dimension tables (Product, Customer, Date). Since CompanyID is present in both the OrderItem and Product tables, it acts as a foreign key in the relationship. Similarly, ProductID is a foreign key that relates these two tables. To enable analysis by date, product, and customer, the Company entity would need to be denormalized into the Customer and Product entities to ensure that the relevant company information is available within those dimensions for querying and reporting purposes.

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Dimensional modeling

Star schema design

Folding in Power Query refers to operations that can be translated into source queries. In this case, " some " of the steps can be folded, which means that some transformations will be executed at the data source level. The steps that cannot be folded will be executed within the Power Query engine. Custom steps, especially those that are not standard query operations, are usually executed within Power Query engine rather than being pushed down to the source system.

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Query folding in Power Query

Power Query M formula language

To meet the technical requirement that data loading activities must ensure the raw and cleansed data is updated completely before populating the dimensional model, you would need a mechanism that allows for ordered execution. A pipeline in Microsoft Fabric with dependencies set between activities can ensure that activities are executed in a specific sequence. Once set up, the pipeline can be scheduled to run at the required intervals (hourly or daily depending on the data source).

The PoC is planned to be completed using a Fabric trial capacity, which implies that users involved in the PoC should be able to try paid features. However, this should be limited to specific security groups involved in the PoC to prevent the entire organization from accessing these features before the trial is proven successful (A). The ability for users to create Fabric items should also be enabled for specific security groups to ensure that only the relevant team members participating in the PoC can create items in the Fabric environment (E).

You should use CREATE VIEW to make the pricing group logic available for T-SQL queries.

The CASE statement should be used to determine the pricing group based on the list price.

The T-SQL statement should create a view that classifies products into pricing groups based on the list price. The CASE statement is the correct conditional logic to assign each product to the appropriate pricing group. This view will standardize the pricing group logic across different databases and semantic models.