Data mining, a buzzword in the 1990s, is the predecessor of data science (the science of data). One of the methodologies popular in the data mining community is called Cross-Industry Standard Process for Data Mining (CRISP-DM). CRISP-DM was created in 1996 and is still used today. I'm not endorsing CRISP-DM, however, I do like its general framework.
The CRISP DM consists of the following phases, which aren't mutually exclusive and can occur in parallel:
- Business understanding: This phase is often taken care of by specialized domain experts. Usually, we have a business person formulate a business problem, such as selling more units of a certain product.
- Data understanding: This is also a phase that may require input from domain experts, however, often a technical specialist needs to get involved more than in the business...
