MGoldbergatDI writes: There is a debate going on, and many experienced statisticians argue that the secret to taming your big data problems is by embracing the size of your detail data, rather than the complexity of your models. Dozens of articles have been written detailing how more data beats better algorithms. But very few address why this approach yields the greatest return. In this article, Garrett Wu, a former technical lead at Google's personalized recommendations team explains that having more data allows the “data to speak for itself,” instead of relying on unproven assumptions and weak correlations.
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