Clustering is a way to group data without knowing the groups beforehand. The article reviews different clustering methods, like k-means and hierarchical clustering. These methods split data into clusters based on similarities. K-means divides data into k groups, while hierarchical clustering builds a hierarchy of clusters. Density-based algorithms group data based on density, and grid-based algorithms use grids to form clusters quickly. The main goal of the article is to analyze clustering techniques in data mining.