Data Warehouse decentralization strategy

Abstract

A Data Warehouse (DW) is characterized by a huge amount of data centralized in a single database. This centralization has negative impacts on its performance especially for distributed companies; such us elevated storage cost, high query execution time and hard maintenance task. Since a relational data warehouse has the same physical structure as a classical database, it can enjoy all the benefits realized during the past in distributed databases like data availability, simplicity, rapid local data access and transparent access to remote sites. Then, it would be interesting to manage and test its decentralization on several distant sites. However, very few studies have considered this topic. In this paper, we present a relational DW decentralization strategy. We show experimentally with the use of the APB-1 release II benchmark that DW decentralization gives better performance than the centralized context. Global queries execution time is reduced by 80%. © 2010 IEEE.