Title: Bridging Decision Applications and Multidimensional Databases

Abstract:
Data warehouses were envisioned to provide an architectural model for the flow of data from operational systems to decision support environments in order to facilitate reporting and analysis. The multidimensional models created for decision support systems represent the conceptual view of the data warehouse the designer has. Typically, there is an impedance mismatch between this conceptual view and the physical representation of the multidimensional data. In addition, this gap between conceptual and physical schemas might cause some heterogeneity in data instances. We present a framework in which the relation of
the conceptual model and multidimensional data are specified by a set of attribute-to-attribute mappings, which are compiled into a set of views that associate each construct in the conceptual model to a query on the physical model. Our approach refactors the dimensions in the conceptual schema and partitions its data instances in order to extract a set of summarizable dimensions.