An Application of Rough Set Theory to Modelling and Utilising Data Warehouses

A data warehouse often accommodates enormous summary information in various granularities and is mainly used to support on-line analytical processing. Ideally all detailed data should be accessible by residing in some legacy systems or on-line transaction processing systems. In many cases, however, data sources in computers are also kinds of summary data due to technological problems or budget limits and also because different aggregation hierarchies may need to be used among various transaction systems. In such circumstances, it is necessary to investigate how to design dimensions, which play a major role in dimensiona1 mode1 for a data warehouse, and how to estimate summary information, which is not stored in the data warehouse. In this paper, the rough set theory is applied to support the dimension design and information estimation.