Data exploration is an interaction with a data set in search of patterns, like trends, similarities and outliers. Though exploration is applicable to data sets of any size or type, its semi-manual nature makes it more reasonable for smaller data sets, especially those in which the data has been carefully gathered and constructed. Of course, a major advantage of a manual approach is that the mechanisms utilized do not, by design, prevent you from exploring particular aspects of your data. The automated methods like data mining are forever limited by their particular design, which is remind us of “eternal” ad-hoc problem, solved by Visual Drill-down functionality.
Interactive Visualization of Data greatly improves the effectiveness and results of Data Exploration processes.