Multiple-Criteria Approach to Optimisation of Multidimensional Data Models

Article type: Research Article

Authors: Korelič, Igor^{1; *} | Mirchevska, Violeta³ | Rajkovič, Vladislav² | Kljajić Borštnar, Mirjana² | Gams, Matjaž³

Affiliations: [1] Result, Računalniški sistemi d.o.o., Slovenia | [2] Faculty of Organisational Sciences, University of Maribor, Slovenia | [3] Jožef Stefan Institute, Slovenia, e-mail: igor.korelic@result.si

Correspondence: [*] Corresponding author.

Abstract: This paper presents a novel approach to the adaptation of multidimensional data models to user-specific needs. The multidimensional data models used in contemporary business-intelligence systems are inherently complex. In order to reduce the complexity of these models, we propose using a qualitative multiple-criteria decision modelling method that is based on using a hierarchical tree of the criteria to decompose the larger problem into a group of smaller problems. The final value is derived by aggregating the criteria values using simple “if-then” rules, which form the knowledge-based expert rules in the hierarchical criteria tree that reflect users’ preferences. The multiple-criteria analysis of the multidimensional model structure results in a multidimensional model that exhibits a reduced complexity and is adapted to users’ needs. The model was validated using sales data from a medium-size enterprise. The qualitative (through questionnaires) and the quantitative (through usage mining) evaluation of the proposed methodology both showed that the proposed approach increases the ease-of-use of business intelligence systems and also contributes to a higher user satisfaction.

Keywords: data warehousing, multidimensional data model, automatic construction, user profile oriented, multiple-criteria decision analysis

Journal: Informatica, vol. 26, no. 2, pp. 283-312, 2015