Decision Support System Based on Data Warehouse

Abstract

Typical Intelligent Decision Support System is 4-based, its design composes of Data Warehouse, Online Analytical Processing, Data Mining and Decision Supporting based on models, which is called Decision Support System Based on Data Warehouse (DSSBDW). This way takes ETL,OLAP and DM as its implementing means, and integrates traditional model-driving DSS and data-driving DSS into a whole. For this kind of problem, this paper analyzes the DSSBDW architecture and DW model, and discusses the following key issues: ETL designing and Realization; metadata managing technology using XML; SQL implementing, optimizing performance, data mapping in OLAP; lastly, it illustrates the designing principle and method of DW in DSSBDW. Keywords—Decision Support System, Data Warehouse, Data Mining. I. DECISION SUPPORT SYSTEM AND DATA WAREHOUSE A. Decision Support System (DSS) Traditional DSS generally is consisted of three bases model, and IDSS ( Intelligent Decision Support System ) is consisted of four bases structure[1], based on three bases increasing the knowledge base system and its reasoning system, the IDSS is considered of an increase of expert system in the general DSS. Knowledge base is intelligent component in IDSS, used to simulate some smart activity in the human decision making process, that can make DSS supporting to decision makers been greatly enhanced. B. Data Warehouse (DW) B.1 Composition of the DW system DW system contains three levels of architecture, as shown in figure 1. The three levels respectively: data sources, data storage and management , OLAP(On-Line Analytical Processing)and data mining tools. B.2 Data organization structure of DW The data organization style of DW contains three kinds:virtual database relations based on the storage and multidimensional databases. Data Warehouse, the data is divided into four categories: Early details, the details, light degree integrated, highly integrated level. Data Warehouse, there is an important data-metadata (metadata). The data storage environment, there are two main metadata: The first is the operational environment to the data warehouse and conversion of $data, including all source data of members, properties and the data warehouse in the transformation and the two million data for the OLAP and Data Warehouse building map.Figures C. DSS Architecture based on DW DSSBDW[2] (Decision Support System Based on Data Warehouse) compared with traditional DSS, it provided three kinds of decision tools:MDSS(Model DSS), DM, OLAP. The figure 2 can be seen, DSSBDW including DW, Model Analyzing, metadata, OLAP, user interface,etc. II. THE KEY TECHNOLOGY OF DW IN DSS