Analytical synopses for approximate query answering in OLAP environments

In this paper we present a technique based on an analytical interpretation of multi-dimensional data and on the well-known Least Squares Approximation (LSA) method for supporting approximate aggregate query answering in OLAP environments, the most common application interfaces for a Data Warehouse Server (DWS). Our technique consists in building data synopses by interpreting the original data distribution as a set of discrete functions. These synopses, called Delta-Syn, are obtained by approximating data with a set of polynomial coefficients, and storing these coefficients instead of the original data. Queries are issued on the compressed representation, thus reducing the number of disk accesses needed to evaluate the answer. We also provide some experimental results on several kinds of synthetic OLAP data cubes.