With the increasing variety, volume, and velocity of big data, business goals have become more ambitious, complex, and larger in scope. This, in part, explains the growing movement to use scientific modeling approaches. Along with the promise and potential of models are also the pitfalls associated with putting too much blind faith in their outputs. Models can fail suddenly with dramatic impact or they may consistently underperform, leading to significant costs over time.
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