High-Dimensional OLAP: A Minimal Cubing Approach Xiaolei Li, Jiawei Han, and Hector Gonzalez   View Paper (PDF)   Return to RESEARCH SESSION 14:DATA WAREHOUSING Abstract Experience tells us that although data analysis tasks may involve a high dimensional space, most OLAP operations are performed only on a small number of dimensions at a time. Based on this observation, we propose a novel method that computes a thin layer of the data cube together with associated value-list indices. This layer, while being manageable in size, will be capable of supporting flexible and fast OLAP operations in the original high dimensional space. Through experiments we will show that the method has I/O costs that scale nicely with dimensionality and that are comparable to the costs of accessing a fully materialized data cube. ©2005 Association for Computing Machinery