Intelligent Rollups in Multidimensional OLAP Data

In this paper we propose a new operator for advanced exploration of large multidimensional databases. The proposed operator can automatically generalize from a specific problem case in detailed data and return the broadest context in which the problem occurs. Such a functionality would be useful to an analyst who after observing a problem case, say a drop in sales for a product in a store, would like to find the exact scope of the problem. With existing tools he would have to manually search around the problem tuple trying to draw a pattern. This process is both tedious and imprecise. Our proposed operator can automate these manual steps and return in a single step a compact and easy-to-interpret summary of all possible maximal generalizations along various roll-up paths around the case. We present a flexible cost-based framework that can generalize various kinds of behaviour (not simply drops) while requiring little additional customization from the user. We design an algorithm th...

• Type: Conference
• Year: 2001
• Where: VLDB
• Authors: Gayatri Sathe, Sunita Sarawagi
• Keywords: Large Multidimensional Databases, Problem Case, Specific Problem Case, VLDB 2001