An integrated architecture for OLAP and data mining.
Zhengxin Chen · Knowledge Discovery and Data Mining · 1999
Data mining and online analysis processing (OLAP) are two complementary techniques for analysis of large amounts of data in data-warehouse environments to deal with decision-support queries. In this chapter we have examined the gap between these two techniques, and proposed a feedback sandwich model to combine OLAP and data mining. An integrated architecture has also been proposed. Our model and architecture differ from other proposals in that they take care of the overall process of OLAP and data mining, offer flexibility for both loosely-coupled and tightly-coupled combinations of OLAP and data mining (because no particular structure of the extended OLAP/data-mining engine is specified) and allow the feedback of discovered knowledge to enhance future OLAP/data mining. We hope that the opinions presented in this chapter will stimulate more research efforts on the integration of OLAP and data mining.