Clustering Analysis

Clustering or cluster analysis is used to group similar data points based on selected features.

To perform clustering, a data analyst might normalize the data, select an algorithm such as K-means or hierarchical clustering, and determine the optimal number of clusters using techniques like the elbow method.

While analysts can't really predict the exact insights they'll get out of this practice, chances are, they'll likely have their own theories. The resulting clusters, of course, will be the ones that reveal hidden patterns, such as customer segments or regional sales performance groups, leading to valuable insights.