Scatterplots matrix is still one of the most popular and widely used approaches to explore multi-dimensional datasets with the advantages of simplicity and clarity. However, this technique is suffering from some shortages. It will result in clutter when displaying large complex datasets, because the data points overlap each other. In addition, it’s difficult to convey more information except the distributions between two dimensions. This paper improves and extends the current scatterplots to address these shortcomings. a) It glances at the scatterplots matrix and emphasize its single unit by overview + detail. b) It uses clustering algorithm to divide all the points in a scatterplots into several groups to avoid confusion. c) Bar axis instead of line axis is used to illustrate the density on each dimension, conveying more information. d) Histogram is another approach to express the same data feature with bar axis. e) Several interaction techniques are adopted to adjust the visualization. Finally, some scenarios are created to argue that this approach is available and effective. This approach is helpful in visualizing and analyzing the large complex data sets in the area of finance and industry.