The Design And Realization Of CRM System Analyzing Function Based On Data Mining Technology

With the rapid development of computer technology and the constantly renewed needs of enterprises, database technology has emerged. Traditional database technology is merely database sources, dealing with different kinds of data processing works, such as transaction processing and batch processing, base on the database. Database Technology greatly pushed forward the rapid development of computer application. Further more, the development of OLAP technology and DM technology also has enlarged the scope of database application.This thesis introduced the general researching of Data Mining, including the definition of data mining, the relations between data mining and other sciences, the main mining processing, sorting and main technical measures. In addition, the thesis also introduced the research of relating rules mining by using some instances, and at the same time original model system and commercial products as well as their application. The thesis pointed out the challenge and current limitation of data mining research. Combing the current database development, the thesis probed into the characteristics and potential of data mining under database environment. By comparing Data Mining, OLAP and DSS, the thesis deeply analyzed Data Mining value.Today, Data Mining technology has been accepted and used by the industry. Combining with the specific application, which is Heilongjiang Post Customer Relations Management Center (confirmed by National Postal Office as Science Research Project), the thesis deeply probed into the value of Data Mining Technology for managing development of enterprises. At the end, the thesis emphasized the relating analysis, which is based on quantity, and probed deeply by using examples (Heilongjiang Post Deposit Bureau, Express Mail Service).The instances and data, which are given in the thesis, are all based on the practice, and have been reconstructed further. With the accumulation of electric data of application units, the researching result must be better reflecting the value of Data Mining in practical application.