CRISP-DM, which stands for “Cross Industry Standard Process for Data Mining” is a proven method for the construction of a data mining model.
The methodology’s assumption is the willingness to make the process of data mining reliable and usable by people with few skills in the field but with a high degree of knowledge of the business. The methodology provides a framework that includes six stages, which can be repeated as in a loop with the aim to review and refine the forecasting model:
- Business Understanding
- Data Understanding
- Data Preparation
- Modelling
- Evaluation
- Deployment
Work on defining the standard began in 1996 as an initiative funded by the European Union and carried out by a consortium of four companies: SPSS, NCR Corporation, Daimler-Benz, and OHRA.
The first version of the methodology sees the light in 1999, while studies to define the standard CRISP-DM 2.0 began in 2006. However, the second version has never seen the light and no sign of activity or communication was received by the team since 2007, and the website has been inactive for quite some time now. Despite this, the CRISP-DM methodology is valid and it has been widely adopted by companies that have adopted data mining projects.
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