In this edition, we will explore the art of uncovering hidden patterns in your data using KMeans and DBSCAN. By the time you finish reading, you’ll have a clear sense of how each algorithm thinks, how to decide which one fits your data, and how to interpret the clusters they create. You’ll observe how KMeans brings structure and precision, while DBSCAN adds flexibility and adaptability for messier, real-world data. We’ll also bring in UMAP, a powerful tool that turns complex, high-dimensional data into something you can actually understand.

Discover how to create, test, and publish Microsoft Fabric Data Agents in minutes—no code required and no guesswork.  This article will have you saying “wow, that was easy!" in no time.