A method for visualization the correlation-based data has been investigated. The advantage of this method lies in the possibility to restore the system of multidimensional vectors describing parameters from their correlation matrix (one vector for one parameter) and to visualise these vectors for the visual decision making on the similarity of the parameters. The goal of this research is to investigate the possibility to reduce the dimensionality of the vectors from the restored system and to evaluate the visualization quality in dependence on the reduction level.