A very well-known modeling process is CRISP-DM for data mining and predictive analytics projects, and it involves six steps:
- Business understanding
- Data understanding
- Data preparation
- Modeling
- Evaluation
- Deployment
Each of these phases follows each other, and some of them happen in a recursive fashion by providing feedback to the preceding phase. The deployment phase is particularly important in terms of model monitoring and maintenance, which is the focus of this chapter.
Let's quickly look at each of these phases and their purpose in the overall process.