Models of multi-dimensional analysis for qualitative data and its application

Abstract

Online analytical processing (OLAP) is one of the technologies that enable client applications to efficiently access data multi-dimensionally. This powerful tool helps users create new views of data, based on a rich array of ad hoc calculation functions. However, the complexity of queries required to support OLAP applications in the multi-dimensional model makes OLAP difficult to implement by simply using standard relational database technology in a static manner. Moreover, OLAP requires numerical data input. In contrast, qualitative data cannot be operated on using OLAP technique. This paper develops models of multi-dimensional analysis, based on traditional multi-dimensional techniques and OLAP techniques to analyze qualitative data dynamically. The models are able to discover the kernel knowledge from the current formulated knowledge. The proposed model is used to develop multi-dimensional algebra to facilitate operation in data warehouse. © 2005 Elsevier B.V. All rights reserved.