A Power BI report named Sales uses an Excel data source with a flat table containing ProductID, ProductColor, ProductName, ProductCategory, and SalesAmount. You want an optimal fact table in a star schema. Which two columns should remain part of the new fact tables?

A Power BI report named Sales uses an Excel data source with a flat table containing ProductID, ProductColor, ProductName, ProductCategory, and SalesAmount. You want an optimal fact table in a star schema. Which two columns should remain part of the new fact tables?

• A. ProductID and SalesAmount
• B. ProductColor and SalesAmount
• C. ProductName and ProductCategory
• D. ProductID and ProductName

Answer: (A)

In a star schema, the fact table stores the numeric measures and the foreign keys to dimension tables. For a sales fact, SalesAmount is the measure, and ProductID serves as the key to the Product dimension. The other attributes—ProductColor, ProductName, ProductCategory—are descriptive details of the product and belong in the Product dimension, not in the fact table. Keeping only the measure and the corresponding key in the fact table reduces redundancy and supports efficient joins to the dimension. So the two columns that should stay in the new fact table are ProductID and SalesAmount.

In a star schema, the fact table stores the numeric measures and the foreign keys to dimension tables. For a sales fact, SalesAmount is the measure, and ProductID serves as the key to the Product dimension. The other attributes—ProductColor, ProductName, ProductCategory—are descriptive details of the product and belong in the Product dimension, not in the fact table. Keeping only the measure and the corresponding key in the fact table reduces redundancy and supports efficient joins to the dimension. So the two columns that should stay in the new fact table are ProductID and SalesAmount.