Massive Data Cleaning And OLAP Technology In The Tax System

Nowadays, Management Information System (MIS) is widely used in many fields with the development of computer application techniques and theories, which also accumulated large amounts of historical data. With the growth of business data, the complexity of the business to enhance the data quality issues have become increasingly prominent. When people aware of the importance of data quality problems need to be solved, the researchers will develop a framework for detection and cleaning of data quality issues and ideas. Many database vendors developed based on these frameworks and ideas of their own data cleansing tools. With the implementation of the theory and application of cleaning tools and cleaning for the enhancement of the quality of data has played a good role, which reflects the importance of data cleansing.Guizhou Provincial tax data set after the project before the need to focus on the nine city (state, region) and a province directly under the tax data cleaning has been focused on the provincial tax data also need to do the cleaning work. One of the four modules Guizhou rent multidimensional analysis module as the concentration of the provincial bureau project, its main function is to provide for the the Guizhou local tax staff the macro tax data, in order to provide the data base for its decision analysis. This article describes the the Guizhou rent cube tax analysis and decision subsystem functions and characteristics, and presents a selection of programs in the pre-project development process. As one of the major aspects of the subsystem, the organization of multi-dimensional data is particularly important. In the fourth chapter, detailed description of how to create a cube and the cube to develop workflow features according to the of Guizhou local tax cube. Guizhou rent tax data exists in the process of organization of multidimensional data, taking into account data quality issues need further cleaning concentrate for cleaning and processing the data to the provincial bureau. Cube of its dimension and fact tables, which not only involves a few big returns, but also to the code table. Need rules in turn be cleaned. Required for the system to create a cube.The same time, the data cleaning process, for the various technical and difficult issues, such as:How to properly develop cleaning rules, how reasonable dimensions of the cube grading. The proposed solutions.