Transforming non-covering dimensions in OLAP

Abstract

OLAP (On-Line Analytical Processing) systems are used to support decision-making processes by providing agile analytical operations on large amounts of data. Usually, the operations require dimensions to be onto and covering; however, in real-world applications, many dimensions fail to meet the requirements, which can be non-covering, non-onto or self-into. In this paper, we will mainly concern the transforming of non-covering dimensions; we first define four different types of non-covering dimensions, and then devise several algorithms to transform them into covering ones respectively. The algorithms are of low computational complexity and can provide full support for transforming various non-covering dimensions into covering ones correctly. © Springer-Verlag Berlin Heidelberg 2005.