OLAP Analysis Operators for Multi-State Data Warehouses

Franck Ravat, Jiefu Song and Olivier Teste
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Franck Ravat: Toulouse Institute of Computer Science Research - Toulouse I Capitole University, Toulouse, France
Jiefu Song: Toulouse Institute of Computer Science Research - Toulouse I Capitole University, Toulouse, France
Olivier Teste: Toulouse Institute of Computer Science Research - University of Toulouse-Jean Jaurès, Toulouse, France

International Journal of Data Warehousing and Mining (IJDWM), 2016, vol. 12, issue 4, 20-53

Abstract: Data reduction in Multidimensional Data Warehouses (MDWs) allows increasing the efficiency of analysis and facilitating decision-makers' tasks. In this paper, the authors model a MDW containing reduced data through a set of states. Each state is valid for a certain period of time; it contains only useful information according to decision-makers' needs. In order to carry out analyses in a MDW composed of multiple states, an extension of traditional OLAP analysis operators is required. In this paper, the authors define a set of OLAP operators compatible with reduced MDWs. For each operator, they propose a user-oriented definition along with an algorithmic translation. To show the feasibility and the efficiency of the proposed concepts, they implement the analysis operators in an R-OLAP framework.

Date: 2016
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