Discovery-driven exploration of OLAP data cubes

Abstract

A method for locating data anomalies in a k dimensional data cube that includes the steps of associating a surprise value with each cell of a data cube, and indicating a data anomaly when the surprise value associated with a cell exceeds a predetermined exception threshold. According to one aspect of the invention, the surprise value associated with each cell is a composite value that is based on at least one of a Self-Exp value for the cell, an In-Exp value for the cell and a Path-Exp value for the cell. Preferably, the step of associating the surprise value with each cell includes the steps of determining a Self-Exp value for the cell, determining an In-Exp value for the cell, determining a Path-Exp value for the cell, and then generating the surprise value for the cell based on the Self-Exp value, the In-Exp value and the Path-value.

Dependencies are inferred from the claim text.