Business Intelligence Technology And Its Application For Rural Credit Union

With the development and popularization of the computer, the success of relational database systems, a variety of database systems which have been developed is widely used in various industries by an unprecedented rate, which makes the transaction more accurate and efficient. Moreover, the enterprise daily data is rapid growing exponentially. Although there is big large of data, the real decision-makers and analysts feel the information is poor when they need to analyze and make a decision. They are unable to start and don’t know how to apply the information. Demand-driven business intelligence technologies:data warehousing, online analytical processing and data mining have been the rapid development of technology, which is now becoming a pillar of the data explosion era.Rural credit cooperatives is the basis of rural financial system. Only deepen the reform of rural credit cooperatives, thereby rural financial services can be improved, and development of rural credit cooperatives can be healthy and stable. These are related to farmers’income, agricultural development, rural’s stability. However, there is currently a huge loss of customer problems in rural credit cooperatives, which has seriously affected the normal development of rural credit cooperatives. As of RCU operators, customer churn is a major problem in the increasingly competitive market for all financial institutions, how to find the reason for the loss of customers, how to effectively reduce churn, reducing the loss of a large number of funds, have become the important problem in RCU.Although business intelligence technology research and application in the banking industry is so many, due to the special circumstances of rural credit cooperatives, face to different customers, make the theories and models studied by predecessors apply to RCU is not very good. In addition, in the process for creating a data warehouse, some of the key design methods and techniques are introduced too little. In the data warehouse design process, there are still many problems. In this paper, and data warehouse construction project of a rural credit cooperatives as an opportunity and business intelligence and customer relationship management theory as a framework, some of the key technologies in detail are researched.and the data is used in customer churn, and we get a churn prediction model to predict better. Now the relevant content are summarized as follows:1. we make a practice in data warehouse design, the reason and principles of design is more clearly. Including:project needs analysis, logical model design, physical model design, ETL design and development.2. the business logic for RCU, such as:the logic of party themes is analyzed in detail, and then found that the parties need to have the design sub-themes.the tables included by sub-themes, the fields included by tables, have done a detailed study and description.3.In this paper, we use the data obtained in the project to build churn modeling, and expect to be able to identify the characteristics of customer churn and reduce customer churn, and improve the effectiveness of rural credit cooperatives. In modeling, we use the classic decision tree analysis method in data mining to establish the model of customer churn.