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Step-by-step data mining guide Pete Chapman (NCR), Julian Clinton (SPSS), Randy Kerber (NCR), Thomas Khabaza (SPSS), Thomas Reinartz (DaimlerChrysler), Colin Shearer (SPSS) and Rüdiger Wirth (DaimlerChrysler)

SPSS is a registered trademark and the other SPSS products named are trademarks of SPSS Inc. All other names are trademarks of their respective owners. © 2000 SPSS Inc. CRISPMWP-1104

This document describes the CRISP-DM process model and contains information about the CRISP-DM methodology, the CRISP-DM reference model, the CRISP-DM user guide, and the CRISP-DM reports, as well as an appendix with additional related information. This document and information herein are the exclusive property of the partners of the
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Over the next two and a half years, we worked to develop and refine CRISP-DM. We ran trials in live, large-scale data mining projects at Mercedes-Benz and at our insurance sector partner, OHRA. We worked on the integration of CRISP-DM with commercial data mining tools. The SIG proved invaluable, growing to over 200 members and holding workshops in London, New York, and Brussels. By the end of the EC-funded part of the project—mid-1999—we had produced what we considered a good-quality draft of the process model. Those familiar with that draft will find that a year later, although now much more complete and better presented, CRISP-DM 1.0 is by no means radically different. We were acutely aware that, during the project, the process model was still very much a work-in-progress; CRISP-DM had only been validated on a narrow set of projects. Over the past year, DaimlerChrysler had the opportunity to apply CRISP-DM to a wider range of applications. SPSS’ and NCR’s Professional Services groups have adopted CRISP-DM and used it successfully on numerous customer engagements covering many industries and business problems. Throughout this time, we have seen service suppliers from outside the consortium adopt CRISP-DM, repeated references to it by analysts as the de facto standard for the industry, and a
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