The Design And Implementation Of Post Customer Relationship Management System

The current post customer system is composed of some simple and isomeric information systems, which collects various data essential to customer management. In fact, the system can't support data analysis due to its inefficiency in data processing. It becomes more and more challenging to integrate those systems and realize data processing, which will enhance the efficiency in data management, tap the full potentials of data, promote the efficiency of post subscription service, and therefore guide the effective decision-making of post customer relationship management.Data Warehouse, Online Analytical Processing and Data Mining became a focus in recent decision-making research. Data Mining means to mine the data in the data source with its kinds of algorithms, to obtain the knowledge and rules behind the data. The whole process of Data Mining includes the following steps. First, pre-process the data in vary heterogeneous data sources throw ETL to obtain integrated and consistent data. These data are put in a data warehouse in the form of multi-dimension form. Second, maintain and manage the data in the data warehouse. Third, OLAP analysis and Data Mining are made on the data. Last, display the results of analysis and mining in the forms of reports, charts and graphs, which may be used by users to make decision support.The thesis designs a periodical customer relationship management system based on a in-depth analysis of customer management. Besides, the thesis gives a full description of research and development systematic data warehouse, module designs, and realization of all functions.The final result of research and development demonstrates the reasonable and effective system design that gives a feasible method in enhancing the post customer relationship management and providing a better service.