CRM Application Of Data Warehouse

The rapid growth of E-commerce presents a severe challenge for the traditional enterprises, which requires enterprises to regard clients with new thinking. In this background, customer relationship management has been widely used and developed, which provides enterprises application system to collect,analyze and exploit customer information,and scientific methods to manage customers. It changes company's marketing concept from product-centric to customer-centric. Traditional CRM information systems produce a large amount of customer characteristic information and customer behavior information, but the information is only limited to original data records and lack of deep analysis, with increasing firm size and volume of basic data, management of customers become more and more difficult. Therefore, the application of data warehouse technology to build an analytical CRM system is particularly important.Integrated data warehouse is a data analysis technique. It can integrate all levels of data in enterprise database together and eventually form a data cube to show to end users. It can realize multi-dimensional analysis, and provide decision-making information for enterprise managers fast and intuitively. It becomes a powerful tool for decision-making. As the basic core of CRM, data warehouse will become more important in the field of business intelligence in future.This paper studies the application of data warehouse technologies in enterprise CRM. According to the particular background of technologies application data warehouse with themes of customers, orders and others are built, using SQL Server 2000 to provide powerful storage and retrieval. This work takes open source OLAP engine Mondrian as the OLAP server o provide powerful multi-dimensional analysis, and employs OPENI as the front end of the analysis tools to provide multi-dimensional front-end display. Finally analytic CRM based on data warehouse technologies CRM. Multi-dimensional analysis customer value, customer classification and customer churn. It provides information to support decision-making for enterprise managers, and verify the validity of these models and methods in the application.