Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.
-George Edward Pelham Box
Today, we are at a juncture in which many different types of skill sets are needed to participate in predictive analytics projects. Once, this was the pure domain of statisticians, programmers, and business analysts. Now, the roles have expanded to include visualization experts, data storage experts, and other types of specialists. Yet, so many are unfamiliar with an understanding of how predictive analytics projects can be structured. This lack of structure can be inhibited by several factors. Often there is a lack of understanding of the critical parts of a business problem, and a model is developed much too early. Alternatively, a formal methodology may be put off to the future, in favor of a quick solution.
In this chapter...
