Business Intelligence System Research Based On The ACP Approach

With the global economic development and technological advances, the development ofbusiness dependents on information technology tools. As the information tool of commercialarea, business intelligence is becoming more and more popular and perfect. In today’scompetitive environment, it is important for enterprise to analyze data to predict market trendsand to improve enterprise performance. Enterprises use business intelligence system whichincludes data warehouse, OLAP system and data mining techniques to deal with massivehistorical data, analyze data and get knowledge. So business intelligence is becoming a newhotspot.In this paper, we will combine the ACP approach with business intelligence system tobuild up a new system. The ACP (Artificial systems/societies, Computational experiments andParallel execution) approach provided us an opportunity to use various methods in modelingand analyzing a complex system with intelligent algorithms. We can build up artificialsystems to reflect how the actual systems could be running. Computational experiments areperformed to analyze different scenarios or different configurations of the system. The parallelexecution provides a mechanism for using the results from the experiments on the artificialsystems to guide the real system.In this paper, we present a new method to solve real business problems by building up aquotation system and offering predictive analytics implementations for S company. Contentsof this paper can help improve the data processing efficiency and working efficiency ofenterprise. Also, it has a very major substantive significance.