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Poll: Current
What main methodology are you using for your analytics, data mining, or data science projects ? [200 votes total]

SEMMA (17)
KDD Process (15)
My organizations' (7)
My own (55)
A domain-specific methodology (4)
Other, not domain-specific (16)
None (0)

Total Comments 6 | Start A New Comment
Post Info Comment
Posted By: Gregory Piatetsky, Editor

Posted On: 13 days ago
Views: 446
Business Understanding

Ralph, Business (domain) understanding is not binary - you can always have more! Part of the knowledge discovery and CRISP-DM process is to increase your business understanding

Posted By: Ralph Winters

Posted On: October 16th
Views: 449
Business Understanding

I always thought of the Business Understanding part as a chicken or egg problem. You either have it and you can mine it, or you need to mine it to define it, if you don't.

Posted By: James Taylor

Posted On: October 15th
Views: 535
Decision Modeling

I like CRISP-DM because it puts business understanding front and center at the beginning of the project. We have had some success with using decision modeling - based on the new Decision Model and Notation standard - as a way to express understanding of the business problem by modeling the decision that the analytic is designed to improve. More focused than simply saying "improve this metric", decision modeling helps focus analytic projects on improving the way the business acts today while providing great assets for planning deployment and adoption.
See http://decisionmanagementsolutions.com/decision-modeling-for-predictive- analytic-projects for more.

Posted By: Martin Jetton

Posted On: October 14th
Views: 625

Robin Way, in his model deployment red paper, outlines a very nice ongoing methodology that covers not just model deployment but model maintenance as well. Model maintenance is a very important aspect for financial institutions.

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