Dataanalysis Of Telecom CRM System Based On J2EE

At present, the rapid development of computer technology, the competition between enterprises is becoming more and more intense.Companies want to get advantage in the competition, must improve management performance and management efficiency. Telecom industry is no exception, especially for the telecommunications industry customer relationship management(CRM), the management level and management efficiency directly affects the enterprise the competitive ability. Many telecommunications companies realize the importance of customer relationship management, invest a lot of manpower material resources to build a CRM system, but most did not take into account the age of big data massive telecom data capacity of growth brings to the traditional telecom CRM system scalability problems, lead to inefficient telecom CRM data mining processing. In the light of the efficient management and massive telecom CRM data mining needs, and the use of advanced application development framework, using big data processing technique put forward feasible solutions and implementation of construction.This article mainly city telecom CRM management and miningsystem construction as the carrier, in the full analysis of the problems in the current telecom CRM system, based on the integrated use of management science, psychology, performance management, such as knowledge, design and implement a set of telecom CRM system management and mining. In order to make the telecom operators can have more customers and make the decision makers to develop new plans and implementing cross-selling has substantial scientific basis, this paper through the clustering algorithm to the customer group, in the group of customers to identify the decline in the telecommunications industry business customers. Through to the decline in business customers consumer behavior and analyze customer information, to capture customer churn, according to different customer churn reason making accurate customer marketing solutions and customer retention, so as to achieve the purpose of reduce customer churn rate. At the same time,through the association rule algorithm to realize the related formula recommended sales and cross-selling. With the rapid growth of massive telecom user data, analysis of the traditional clustering algorithm and association rules method already can not adapt to such a massive telecom user data processing and analysis, this paper based on Hadoop platform of mass data processing method for the analysis of user data, make decisions to provide effective support to the telecom industry departments, such as the choice of marketing strategy, business recommendation modelprediction model and new business growth point, etc. This article by graphs algorithm implementation of a K- means algorithm and Apriori algorithm, not only improve the efficiency of the mass data processing,also get conclusions as a guidance for decision making.