OLAP operators for complex object data cubes

Abstract

Nowadays, multidimensional models are recognized to best reflect the decision makers' analytical view of data. The classical multidimensional models were meant to analyze conventional data (numerical and categorical). However, they fail to handle data complexity, which is expressed by the multiplicity of data sources, the heterogeneity of formats, the diversity of structures, etc. To this end, new multidimensional models have been proposed for OLAP purposes. Nevertheless, data complexity is partially covered in these models, which may cause a lack in decision making. In our previous work, we proposed to integrate data complexity within a complex object-based multidimensional model. In this paper, based on our proposed model, we provide adapted OLAP operators that take into account data complexity. Thus, we define operators to create complex data cubes, to visualize them and to analyze them. © 2010 Springer-Verlag.