After explaining how you can reduce your Power BI data model size by 90%, by simply adhering to some simple rules, and understanding how your data model is being optimized by the VertiPaq engine in the background, it’s the right moment to learn one of the core concepts of dimensional modeling.

The role-playing dimension is not a concept exclusively related to Power BI. It’s a universal data modeling technique that comes from Kimball’s methodology.

Simply said, it’s the situation when you use one same dimension for creating multiple relationships to your fact table. Typical usage of the role-playing dimension concept is with the Date dimension since in many cases, your fact table will contain multiple date fields. For example, in the betting industry, there are fields DateBetPlaced and DateBetProcessed, which don’t need to be identical (and in most cases are not). So, let’s say that the business request is to analyze data both on DateBetPlaced and DateBetProcessed.

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