This chapter presents four methods that are designed to explore and summarize large and complex data tables by means of summary statistics: correspondence analysis, multiple correspondence analysis, principal component analysis, and exploratory factor analysis. These methods help generate hypotheses by providing informative clusters using the variable values that characterize each observation.