Scalable Data Mining Systems

The growing number of large data warehouse installations is leading to an increasing emphasis on scalable decision support systems. These are usually thought to be characterised primarily by their use of linear-time algorithms and their ability to exploit parallel processing. This paper argues that other considerations, including integration, data access patterns and “fullprocessing-cycle” speed, are at least as important in constructing scalable decision support systems capable of delivering real business benefits.