When using semantic model extensions to create a dimension in ADW, which fact tables can you join your custom dimension to?

When using semantic model extensions to create a dimension in ADW, which fact tables can you join your custom dimension to?

• A. Only custom facts
• B. Only out-of-the-box facts
• C. No fact tables
• D. Custom fact and out-of-the-box facts

Answer: (D)

When you create a dimension with semantic model extensions in ADW, you establish it as a context for analyzing measures stored in fact tables. The dimension can be joined to both your own custom fact tables and the out-of-the-box (prebuilt) fact tables. This flexibility lets you analyze metrics from either set of facts using the same dimension—slicing and dicing across custom measures as well as those provided by the built-in analytics facts. It wouldn’t make sense to have no fact tables connected, since a dimension gains meaning only through its relationships to facts. Limiting the join to only custom or only out-of-the-box facts would unnecessarily restrict analytic possibilities, whereas joining to both types enables broader, richer analysis.

When you create a dimension with semantic model extensions in ADW, you establish it as a context for analyzing measures stored in fact tables. The dimension can be joined to both your own custom fact tables and the out-of-the-box (prebuilt) fact tables. This flexibility lets you analyze metrics from either set of facts using the same dimension—slicing and dicing across custom measures as well as those provided by the built-in analytics facts. It wouldn’t make sense to have no fact tables connected, since a dimension gains meaning only through its relationships to facts. Limiting the join to only custom or only out-of-the-box facts would unnecessarily restrict analytic possibilities, whereas joining to both types enables broader, richer analysis.