Introduction

Abstract

The progress of data-collection technology, such as bar-code scanners in commercial domains and sensors in scientific and industrial domains, generates huge amounts of data. Moreover, pressure to improve corporate profitability has caused companies to spend more energy in identifying sales opportunities. To aid this task, enterprises increasingly store huge amounts of data in data warehouses for decision-support purposes. [Kelly 95] argues that the needs of decision-support systems are evolving into finer- and finer-grain requirements, in the following manner. In the 60’s the requirements were at the market level; in the 70’s, at the niche level; in the 80’s, at the segment level; and in the 90’s, at the customer level. These finer-grain requirements obviously lead to the use of more data in decision support systems.