Study On Business Intelligence Implimentation In Automobile Industry Chain Platform

With the increasingly fierce market competition and the development of computer technology, information technology has become the inevitable demand of various industries. The required of information access, processing, handling in the business activities is going higher and higher. The traditional operation-based information management system has been difficult to meet the enterprise personalized query, analysis and decision support needs. The concept of business intelligence (BI), which is technically supported by data warehousing (DW), online analytical processing (OLAP) and data mining (DM), is widely recognized by companies.According to the company's business goals, Business Intelligence can convert the business data into a clear, based on facts and be able to conduct information through data analysis and data mining. So it can make the business people to find the trend of sale, increase customer loyalty and prompt new sale opertunity. Business intelligence support of enterprise management and decision-making, help enterprises to improve the competition advantage.The author has deeply analyzed the commen demand of data analysis and decision-support in the collaborative e-commerce platform. And combined with a specific requirement commonness of manufacturing enterprise, author has designed and realized of business intelligence system based on Industrial Chain Collaboration Platform. This system can adapt to the manufacturing enterprise takeing the customer as the center of modern management mode. In the system design process, aimed at specific needs of enterprises, I established sales analysis and decision making for the theme of the data warehouse systems was presented, and the data warehouse multi-dimension data of detailed design and implementation. Then use OLAP service to build of multi-dimension data analysis and display about car sales. In addition, to meet the demand of customer segmentation, we used classical clustering algorithm, and the clustering analysis for the enterprise decision-making personnel customer segment.