Application Of Data Warehouse And Data Mining To Water Supply Company

With the progress of water supply company reform, the enterprise's leaders eager to optimize the productivity by strengthening the information management in order to improve the competition ability. Data Warehouse as a new and realizable way to develop the Decision Support System (DSS), becomes a hot research topic in the domain of database. With the emergence of data warehouse, On-line Analysis Processing (OLAP) technology and data mining technology also comes out. These three technologies provide the powerful and energetic support of data analysis. Thus, the application of DSS based on data warehouse in water supply company will make sense for practice.According to current situation of water supply industry, the paper put forward a rational and feasible method to build a data warehouse in water supply company and implemented relative data analytical processing. The paper did following work:1. The paper looked into the theories and technologies of Data Warehouse, On-line Analysis Processing(OLAP), and data mining, comprehensively and systemically. We built a data warehouse for water supply company, which supports on-line analysis processing and data mining. The paper also illustrated how to build a data warehouse based on Microsoft SQL Server.2. OLAP is the most common and mature analytical method. On the base of analyzing the requirement to the OLAP tool's functions and performance, the paper presented our realization method and developed a real system on Brio Intelligence Business Intelligence platform.3. Waterworks focuses on Water supply, so it is great significant to study an accurate and reliable demand forecasting model. This subject selected support vector machine(SVM) as a tool to predict daily water demand. SVM employs the idea of structural risk minimization which balances the empirical risk minimization and VC dimension to achieve high generalization. It is proved to be efficient.