In the last 20 years improvements in the computer sciences made it possible to store large data sets containing a plethora of different data attributes and data values, which could be applied in different application domains, for example, in the natural sciences, in law enforcements or in social studies. Due to this increasing data complexity in modern times, it is crucial to support the exploration of the hypervariate data with different visualization techniques. These facts are the fundament for this paper, which reveals how the information visualization can support the understanding of data with high dimensionality. Furthermore, it gives an overview and a comparison of the different categories of hypervariate information visualization, in order to analyse the advantages and the disadvantages of each category. We also addressed in the different interaction methods which help to create an understandable visualization and thus facilitate the user’s visual exploration. Interactive techniques are useful to create an understandable visualization of the relationships in a large data set. At the end, we also discussed the possibility of merging different interactions and visualization techniques. Hypervariate Information Visualization