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:
- Business understanding
- Data understanding
- Data preparation
- Modelling
- Evaluation
- Deployment
Following diagram shows the different stages:
Different stages in CRISP-DM
As we can see, it's a continuous process model with data science and AI playing important roles ...
