Application Research Of Data Warehouse And Data Mining In Decision Support System

With the popularization of computer and the great success of relation data base system. various kinds MIS have been developed with unprecedent speed and widely use in many fields. making the processing of affairs more accurate and effective, and the accumulated data increasing with great speed. But data overflow and information shortage still disturb decision makers. As a new applied data base technology and tool, data warehouse and data mining technology, which is more and more popular, becoming the crucial technological element in decision supporting system. On the perspective of the development and demand of decision supporting system, this thesis describes the theory for designing data warehouse and the concept of data mining and its application. With a focus on the construction of data warehouse and the algorithm for association rules of data mining. it also makes a preliminary analysis of the design and the crucial technology of the university data warehouse ,and finished the design of multi-dimension data model of relevant topics. by using university teacher's relevant data, with the result of OLAP analysis demonstrated with three different methods, and detailed description made of the process and extension of MDX. By using the algorithm of Apriori, this thesis accomplishes the construction of the model for mining the relevant rules based on teacher's topic cube, and find the association knowledge to help decision makers, find the information of decision support concerning the recruiting of teachers. Finally, it propose the further construction of data warehouse based on the Web for the timely mining of knowledge and support of decisions.