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A parallel algorithm to compute data synopsis

Business Intelligence systems are based on traditional OLAP, data mining, and approximate query processing. Generally, these activities allow to extract information and knowledge from large volumes of data and to support decisional makers as concerns strategic choices to be taken in order to improve the business processes of the Information System. Among these, only approximate query processing deals with the issue of reducing response time, as it aims to provide fast query answers affected with a tolerable quantity of error. However, this kind of processing needs to pre-compute a synopsis of the data stored in the Data Warehouse. In this paper, a parallel algorithm for the computation of data synopses is presented.