You probably already know that you can do basic clustering in Power BI with the scatter plot. With clustering, you try to find groups of cases, for example typical groups of customers, and also outliers, cases that do not fit well in any of the clusters. The most popular clustering methods include Hierarchical, K-Means, K-Medoid, and Gaussian Mixture Models clustering. This presentation unveils the algorithms behind the different clustering methods and shows how to implement advanced clustering in Power BI with help of custom visuals, and R and Python code. The attendees learn how to use Power Bi for the interpretation of the clusters. Mathematical evaluation of clustering models as an advanced topic is introduced as well.