This session focuses on data modeling with a strong emphasis on real-world scenarios. A solid foundation is assumed: familiarity with the star schema, the importance of correct data types, and the core principles of a well-designed Power BI data model.

During the session, I go beyond theory and show how to make practical design choices when building fact tables. For example, when should you use a snapshot fact table? What types of business questions does it support, and how do you design such a structure correctly?

Slowly Changing Dimensions Type 2 are also covered. I demonstrate how to set up an SCD Type 2 dimension and, more importantly, how to create correct and reliable DAX calculations on top of it. The focus is not only on the technical implementation, but also on the reasoning behind these choices.

Many-to-many relationships are another key topic. What happens when data exists at different levels of granularity? When do issues arise? And is a bridge table always the right solution, or are there alternative approaches, for example when dealing with budget data?

In short, this session goes beyond the classic star schema. It presents practical solutions for realistic modeling challenges, because customer data models are rarely as clean and straightforward as the well-known Contoso example.