Hierarchical clustering is a method used to group things together based on similarities. There are two main ways to do this: agglomerative, where individuals are merged into groups, and divisive, where individuals are split into smaller groups. The results are shown in a diagram called a dendrogram. This chapter focuses on agglomerative techniques and their properties, which can also be applied to divisive techniques. The chapter also discusses some divisive techniques and common issues in both approaches. Overall, hierarchical clustering has many practical applications in various fields.