Cluster analysis is a data analysis technique used to group similar data points into clusters based on their characteristics or attributes. It is commonly used in various fields such as data mining, machine learning, market research, and social network analysis. The goal of cluster analysis is to identify patterns and structures within a dataset, allowing researchers to uncover hidden relationships and gain insights into the underlying data. Different clustering algorithms can be applied depending on the nature of the data and the desired outcomes, such as hierarchical clustering, k-means clustering, or DBSCAN. Overall, cluster analysis helps to organize and interpret large datasets, enabling researchers to make informed decisions and predictions based on the grouped data.