On the Complexity of the Reduction of Multidimensional Data Models

Abstract

In this paper, decomposition methods for multidimensional data hypercubes of OLAP systems are investigated. Criteria for reducing the computational complexity of the decomposition methods are presented and comparisons are made with the traditional solutions of multidimensional data analysis problems. Examples illustrating the application of these criteria to investigating the dynamics of computational complexity changes for specific types of reduction problems are considered.