The Combination of Knowledge Management and Data mining with Knowledge Warehouse

Abstract

Effective knowledge management (KM) enhances products, improves operational efficiency, speeds deployment, increases sales and profits, and creates customer satisfaction. Data warehousing provides an infrastructure that enables business to extract, and store vast amounts of corporate data. The purpose of data warehouse is to empower the knowledge workers with information that allows them to make decision based on a foundation of fact. The aim of this paper is to integrate a framework of knowledge management and data mining with knowledge warehouse. Therefore, first, it will brief review the existing of knowledge management, data mining, and decision support system. We then present on knowledge management or supplementary relationship between the knowledge management, data mining and decision support system with knowledge warehouse. Second, knowledge, knowledge management and knowledge process is defined. Third, we introduce decision support, data mining and data warehouse support of knowledge management, and point out data mining in data warehouse environment. Four, the warehouse is defined. Using this definition, it can drive framework of knowledge warehouse. This framework contain 6 layers: knowledge input, knowledge activity, data store, application server, application system data base, and user client. In this paper some suggestions are made to get knowledge with data mining, which will provide the decision maker with an intelligent platform that enhances all phase of knowledge management and knowledge process.