Data mining techniques and SAS as a tool for graphical presentation of principal components analysis and disjoint cluster analysis results

Complexity of data analysis in data mining often makes results difficult to interpret. This problem could be solved using various approaches. Principal Component Analysis (PCA) and Disjoint Cluster Analysis (DCA) are methods used for data reduction and summarization. In this paper, PCA and DCA were applied on dataset example containing information about students' courses and time necessary to pass related exams. The SAS software was used as a data mining tool for performing this analysis. Another approach for better interpretation is visualization of results. This means showing important attributes visually to aid informal users to interpret results.