A hierarchy-driven compression technique for advanced OLAP visualization of multidimensional data cubes

  • Authors:
  • Alfredo Cuzzocrea;Domenico Saccà;Paolo Serafino

  • Affiliations:
  • Department of Electronics, Computer Science, and Systems University of Calabria, Cosenza, Italy;Department of Electronics, Computer Science, and Systems University of Calabria, Cosenza, Italy;Department of Electronics, Computer Science, and Systems University of Calabria, Cosenza, Italy

  • Venue:
  • DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
  • Year:
  • 2006

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Abstract

In this paper, we investigate the problem of visualizing multidimensional data cubes, and propose a novel technique for supporting advanced OLAP visualization of such data structures. Founding on very efficient data compression solutions for two-dimensional data domains, the proposed technique relies on the amenity of generating “semantics-aware” compressed representation of two-dimensional OLAP views extracted from multidimensional data cubes via the so-called OLAP dimension flattening process. A wide set of experimental results conducted on several kind of synthetic two-dimensional OLAP views clearly confirm the effectiveness and the efficiency of our technique, also in comparison with state-of-the-art proposals.