A Hierarchy-Driven Compression Technique for Advanced OLAP Visualization of Multidimensional Data Cubes

摘要

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.