Based On Data Warehouse Postal Service Finance Customer Management System Design And Realization

Now the world has filled the fierce competition, the correct prompt decision-making is the enterprise survival and the development most important link. Now, the more and more enterprises realized, must want to win in the competition, obtains a greater income, must analyze current and the historical production service data, as well as the correlation environment correlation data, automatically fast gains useful decision information, provides fast, accurate and the convenient policy-making support for the enterprise. But based on the data warehouse business intelligence appearance, becomes solves this question effective way. The business intelligence also is called as BI (Business Intelligence), usually was understood for the existing data transforms the enterprise in as the knowledge, helps the enterprise to make the unwise account executive decision-making the tool, in order to transforms the data as the knowledge, needs to use the data warehouse, on-line analysis processing (OLAP) technology and so on tool and data mining. The data warehouse function lies in "the discovery data value, obtains the repayment from the data". Through the data warehouse, the collection, compiles with analysis enterprise's each kind of data, enhances the working efficiency, provide the better customer service the method. This article logarithm has carried on the discussion according to the warehouse technology in the commercial intelligence application, the main content includes: Elaborated the commercial intelligence concept, the use and the development, and introduced the commercial intelligence project implementation step, has analyzed the enterprise service logic model and the data quality constructs the data warehouse to the success the vital role, and further proved the data warehouse through the postal savings customer management system management system design and the application to raise the enterprise decision-making support level, the information quality, the strain capacity vital significance and the function. Elaborated with emphasis based on the data warehouse business intelligence system overall structural design, the data warehouse system structural design.