Cross Industry Standard Process for Data Mining

CRISP-DM stands for CRoss Industry Standard Process for Data Mining. It is a data mining process model that describes commonly used approaches that expert data miners use to tackle problems.

Major phases
CRISP-DM breaks the process of data mining into six major phases :


 * Business Understanding
 * Data Understanding
 * Data Preparation
 * Modeling
 * Evaluation
 * Deployment

History
CRISP-DM began as a European Union project under the ESPRIT funding initiative. The project was led by four companies, ISL, NCR, Daimler-Benz and OHRA.

This core consortium brought different experience to the project. ISL was the producer of the Clementine data mining software suite, and was later purchased by SPSS. NCR produced the Teradata datawarehouse and its own data mining software. Daimler-Benz (now DaimlerChrysler) had a significant data mining team. OHRA, an insurance company, was just starting to explore how it could use data mining.

The first version of the methodology was released as CRISP-DM 1.0 in 1999.

CRISP-DM 2.0
In July 2006 the consortium announced that it was going to start the process of working towards a second version of CRISP-DM. On 26 September 2006, the CRISP-DM SIG met to discuss potential enhancements for CRISP-DM 2.0 and the subsequent roadmap.

Advantages

 * Industry neutral
 * Tool neutral
 * Closely related to KDD Process Model
 * Anchors the data mining process