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Near real time ETL deviates from the traditional conception of data warehouse refreshment, which is performed off-line in a batch mode, and adopts the strategy of propagating changes that take place in the sources towards the data warehouse to the extent that both the sources and the warehouse can sustain the incurred workload. In this paper, the authors review the state of the art for both conventional and near real time ETL, they discuss the background, the architecture, and the technical issues that arise in the area of near real time ETL, and they pinpoint interesting research challenges for future work.
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