Compressed Data Cube for Approximate OLAP Query Processing

Approximate query processing has emerged as anapproach to dealing with the huge data volume and complex queries inthe environment of data warehouse. In this paper, we present a novelmethod that provides approximate answers to OLAP queries. Our method isbased on building a compressed (approximate) data cube by a clusteringtechnique and using this compressed data cube to provide answers toqueries directly, so it improves the performance of the queries. Wealso provide the algorithm of the OLAP queries and the confidenceintervals of query results. An extensive experimental study with the OLAPcouncil benchmark shows the effectiveness and scalability of ourcluster-based approach compared to sampling.