OLAP In The Research And Application Of Data Warehousing

In recent years, along with the development of database technology and the expanding of database scale, people hope to refine the useful information from existing data to serve for decision; therefore, decision support system emerges as the time require. There have been growing interests in the techniques of data warehouse, OLAP and data mining since they support the decision-making.Both as the important applicative techniques of data warehouse, OLAP and data mining have notable differences. OLAP offers user a view of all angles in order to study the data deeply; however, data mining analyzes the collecting data automatically, makes the including ratiocination and then helps the decision maker to adjust the strategy and to reduce the risk and gain the correct decision. Under this point, this paper studies and implements the multidimensional query analysis system. Main works as follow. We proceed from designing the system function, then describe the system architecture and explain the every module. Based on the study of designing pattern of multidimensional data model, three methods are pointed out. The multidimensional data model of the sample database is designed as star schema. The ETL tool is implemented curtly and the tool is independence on structure in order to make the multidimensional query analysis be independent of data source, thereby, the expansibility of system is enhanced. The techniques of establishment and access for multidimensional dataset are discussed. We implement multidimensional query, including drill up/down, slicing etc, and the update of multidimensional data set by the technique of MDX, ADO MD and DSO. The expression of operation by graphic is also implemented.Concluded the thesis and described the future work.