Cross-industry standard process for data mining

For IoT problems, the most used data management (DM) methodology is cross-industry standard process for data mining (CRISP-DM) proposed by Chapman et al. It's a process model that states the tasks that need to be carried out for successfully completing DM. It's a vendor-independent methodology divided into these six different phases:

1. Business understanding
2. Data understanding
3. Data preparation
4. Modelling
5. Evaluation
6. Deployment

Following diagram shows the different stages:

As we can see, it's a continuous process model with data science and AI playing important roles in steps 2–5.