The Research Of Multi-dimensional Data Model In Data Warehouse

Data warehouse is used for making decision management, data model is one of the center problem in the research of data warehouse. Many research show that tradition data model(for example, entity-relationship model) can not express the data structure and semantic meaning of data warehouse effectively, at the same time, it hardly support on-line analytical processing. So people put forward several multi-dimensional data model in data warehouse are hierarchical and this also leads the logical dimension structure to be hierarchical so that the dynamic characteristics of analysis, which often switches between different levels of dimension, can be better supported. Multi-dimensional data model define the measurement and dimensionality for data warehouse, it is the base of OLAP and some data mining as well as the important measure for data warehouse. But many multi-dimensional data model have insufficiency in express the complicated data structure and semantic meaning as well in operate OLAP has insufficient. This paper based the analysis of the traditional multi-dimensional data model, used the tools include arrangement structure in space, multi-dimensional in space to express the model. This model can express the complicated data structure and semantic meaning for data warehouse fully, perfect and enhance the transact efficiency for OLAP, form dimension and algebra quickly, support the complicated data structure in levels of dimension, provide the restriction-mechanism in polymerization function.