You have a table in ADW and want to create a dimension via Semantic Model Extensions. Which is correct about joining to fact tables?

You have a table in ADW and want to create a dimension via Semantic Model Extensions. Which is correct about joining to fact tables?

• A. Only Custom Fact Tables
• B. Only Out-of-the-Box Fact Tables
• C. Custom Fact and Out-of-the-Box Fact Tables
• D. No Fact Tables Can Be Joined

Answer: (C)

In Semantic Model Extensions, a dimension is designed to be linked to the fact data you want to analyze, regardless of where that data comes from. You can join a dimension to both custom fact tables (your own loaded facts) and out-of-the-box, prebuilt fact tables. This means the same dimension can serve as a common reference across multiple fact sources, enabling consistent filtering and aggregation across the full analytics model. The practical idea is to map the dimension’s key to the corresponding foreign key in each fact table and ensure the data types align. Once those joins are defined, you can run queries that slice measures from either type of fact by the same dimension, making the dimension broadly usable. Thus, the correct approach is to join to both custom fact tables and out-of-the-box fact tables. Conversely, there are valid reasons why the other options don’t fit: limiting joins to only one type would exclude the other, and claiming that no fact tables can be joined contradicts how SME models are designed to connect dimensions to facts.

In Semantic Model Extensions, a dimension is designed to be linked to the fact data you want to analyze, regardless of where that data comes from. You can join a dimension to both custom fact tables (your own loaded facts) and out-of-the-box, prebuilt fact tables. This means the same dimension can serve as a common reference across multiple fact sources, enabling consistent filtering and aggregation across the full analytics model.

The practical idea is to map the dimension’s key to the corresponding foreign key in each fact table and ensure the data types align. Once those joins are defined, you can run queries that slice measures from either type of fact by the same dimension, making the dimension broadly usable.

Thus, the correct approach is to join to both custom fact tables and out-of-the-box fact tables. Conversely, there are valid reasons why the other options don’t fit: limiting joins to only one type would exclude the other, and claiming that no fact tables can be joined contradicts how SME models are designed to connect dimensions to facts.