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OLAP Analysis Operators for Multi-State Data Warehouses

Author

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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)

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.

Suggested Citation

  • Franck Ravat & Jiefu Song & Olivier Teste, 2016. "OLAP Analysis Operators for Multi-State Data Warehouses," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 12(4), pages 20-53, October.
    • Handle: RePEc:igg:jdwm00:v:12:y:2016:i:4:p:20-53
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