An Extended Multidimensional Data Model Supporting Non-Covering Dimensions

A new multidimensional conceptual model is proposed here based on current multidimensional models. The mapping from a parent level to one partition of a child level is defined to support irregular relationships among levels, such as non-covering and non-balanced relationships. Thus, the model can express the semantics of non-covering di- mensions. Moreover, DAG is used to describe a dimensional hierarchy structure. The relationship between views and cubes is discussed explicitly, and the cube algebra and OLAP operation set are also defined. Especially, the transfor- ming operations between dimensions and measures are also imported to enhance the analytical ability of the model.