This project implements canonical correlation analysis between two data matrices. I first create the latent dimensions between the two data matrices. Then I use Kmeans and hierarchical clustering on principal component to group individuals using the latent dimensions and the distance created by the canonical analysis. Last step, I give a profiling of the different groups using descriptive statistics and provide an automated method to export the results.