A Conceptual Model for Combining Enhanced OLAP and Data Mining Systems

Online Analytical Processing (OLAP) was widely used to visualize complex data for efficient, interactive and meaningful analysis. Its power comes in visualizing huge operational data for interactive analysis. On the other hand, data mining techniques (DM) are strong at detecting patterns and mining knowledge from historical data. OLAP and DM is believed to be able to complement each other to analyze large data sets in decision support systems. Some recent researches have shown the benefits of combining OLAP with Data Mining. In this paper, we reviewed the coupling of OLAP and data mining in the literature and identified their limitations. We proposed a conceptual model that overcomes the existing limitations, and provides a way for combining enhanced OLAP with data mining systems. Furthermore, the proposed model offers directions to improving cube construction time and visualization over the data cube.