Study Of Taxation Data Warehouse And Data Mining System

With the rapid progress in the 'building of information, a tremendous amount of data has been generated in taxation bureau. However, these data are place distributed, meaning differentiated, it is hard to turn these data into useful information. They need to be integrated, transformed, cleaned, extracted and loaded to data warehouse which help to change the data into 'knowledge nuggets'. And organizations need the suitable knowledge to operate their business. Building a data warehouse in taxation bureau can help to serve managers more conveniently to make up their decisions.The thesis did some research on how to build taxation data warehouse on the basis of being familiar to the taxation business and it's present information systems. Further, we design the data model and the architecture of taxation data warehouse. On the basis of data warehouse, we design the OLAP system and association rules mining system in order to make deeper data analysis.Some valuable works in the paper include:1. We worked out a new way to update the data warehouse based on inserting timestamp into the database. Many experiments have been done to achieve this new way.2. Analysis Services acts as the server of OLAP which provides capability and good performance and programming interface. Based on the techniques such as ASP.NET, ADOMD, MDX, and TeeChart, we devise a system to present data by tables and graphs based on Web.3. The paper put forward a association rule mining system which allows users to define their mining tasks freely. Meanwhile, some improvements have been done to make the system more efficient:(1) New aggregate functions have been devised,(2) A new prune way was used to make the algorithm more efficient according to the practical mining tasks, such as task relevant data.