Cluster analysis is one of the main methodologies for analyzing multivariate data. While not as neat and tidy as other methods, such as principal components analysis or discriminant analysis, its use is widespread and growing rapidly. The goal of the talk will be to introduce the topic of clustering, document its usage, provide examples of recent applications, and highlight both good and risky practices. It will end with discussion of difficult issues and needs for more research.