Topological Data Analysis provides tools for studying the global structure of data: clusters, loops, holes, branching patterns, and other geometric features that are often difficult to capture using classical statistical methods. In this lecture, we will present, in an informal and intuitive way, examples of tools such as persistent homology, Mapper, Ball Mapper, and Euler characteristic curves and profiles.