This whitepaper outlines new reference architecture for data warehouse optimisation to help organisations speed time to value, maximize productivity, lower costs and minimise risk. • Traditional data warehouse environments are overwhelmed by soaring volumes and varieties of data pouring in • An upgrade is not the most effective way to manage an excess of seldom-used data. To keep pace with exploding data volumes, the data warehouse itself needs to evolve. • One emerging strategy is data warehouse optimisation using Hadoop as an enterprise data hub to augment an existing warehouse infrastructure.
Big data is a major driver of change with its burgeoning size, sources, frequency of delivery, and diversity of structures. This report discusses how data warehouse architectures are evolving. - The adoption of advanced analytics and real-time operation influences data warehouse architectures - Given the rising complexity, DW architecture is more critical than ever in order to make sense of, govern, and optimize complicated multi-platform DWEs - Research was conducted via interviews with industry experts and leading-edge user companies
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