This paper presents a general methodology for the efficient parallelization of existing data cube construction algorithms. We describe two different partitioning strategies, one f...
Frank K. H. A. Dehne, Todd Eavis, Susanne E. Hambr...
—Computing interesting measures for data cubes and subsequent mining of interesting cube groups over massive datasets are critical for many important analyses done in the real wo...
Arnab Nandi, Cong Yu, Philip Bohannon, Raghu Ramak...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP is often supported by a logical structure known as a data cube, a multidimension...
Frank K. H. A. Dehne, Todd Eavis, Andrew Rau-Chapl...