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Recently I have come across a term, CRISP-DM - a data mining standard. Though this process is not a new one but I felt every analyst should know about commonly used Industry wide process. In this post I will explain about different phases involved in creating a data mining solution. 

CRISP-DM, an acronym for Cross Industry Standard Process for Data Mining, is a data mining process model that includes commonly used approaches that data analytics Organizations use to tackle business problems related to Data mining. Polls conducted at one and the same website (KDNuggests) in 2002, 2004, 2007 and 2014 show that it was the leading methodology used by industry data miners who decided to respond to the survey.

CRISP-DM model is a phased approach to tackle a business problem. Different phases involved in the model are defined below:

  • Use case Identification
  • Business Understanding
  • Data Acquisition and Data Understanding
  • Data Preparation
  • Exploratory Analysis
  • Data Modeling
  • Data Evaluation
  • Deployment

For a detailed explanation please visit here

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Comment by suresh kumar Gorakala on November 11, 2015 at 5:28pm

Thanks Williams Vorhies, great to meet you on the forum.

Comment by William Vorhies on October 22, 2015 at 1:05pm

I was part of the original working group to develop CRISP-DM.  It's simple, perhaps obvious, but therefore has stood the test of time.

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