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In this paper we propose a grid-based OLAP application which distributes query computation across an enterprise grid. Our application follows a two-tiered process for answering queries based on sharing cached OLAP data between the users at the local grid site, and using grid scheduling approaches to execute the remaining parts of a query amongst a distributed set of OLAP servers. A new technique for extraction and aggregation of shared cached OLAP data is proposed, along with an efficient, aggregate-aware cache controller. An experimental evaluation of the proposed query processing and cooperative caching methods shows a significant reduction in query times compared to previously proposed methods.