Companies are being pressured on multiple fronts to do something amazing with Big Data. But should the brakes be applied, even slightly, to consider some lessons from the past? Historically, large data warehouse projects failed at surprisingly high rates. How do we learn from these collective past mistakes and increase the odds that Big Data efforts will provide Big Returns?

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