Why do businesses invest in data science applications? “To produce models” isn’t an adequate answer, because models are just bundles of data and code with no intrinsic value. To produce tangible value, applications must have a positive impact on the surrounding world. For instance, a recommendation model is useless in isolation, but when connected to a user interface, it can lower customer churn and increase long-term revenue. Or a model predicting credit risk becomes valuable when connected to a decision-support dashboard used by human decision-makers.
In this chapter, we bridge the gap between data science and business applications. Although this is the second-to-last chapter of the book, in real-life projects, you should start thinking about the connection early on. Figure 8.1 illustrates the idea using the spiral diagram introduced in chapter 3.
