Blog interviews – more predictive analytics FAQs

February 18, 2009
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Here are six recent blog interviews I’ve given about predictive analytics and the Predictive Analytics World conference. These add to the running FAQ I’ve begun here.
Interview by Romakanta Irungbam on DataLLigence

What are the most common mistakes you’ve encountered while working on data mining projects?
Which approaches do you recommend/use to define the acceptable accuracy/cut-off level for […]

Here are six recent blog interviews I’ve given about predictive analytics and the Predictive Analytics World conference. These add to the running FAQ I’ve begun here.

Interview by Romakanta Irungbam on DataLLigence

  • What are the most common mistakes you’ve encountered while working on data mining projects?
  • Which approaches do you recommend/use to define the acceptable accuracy/cut-off level for a data mining project?
  • What are the new areas/domains where data mining is being applied?
  • And more

Interview by John Langford on Hunch.net

  • How fast or difficult is it to transfer academic methods to business use?
  • And more

Interview by Sandro Saitta on dataminingblog.com

  • Data mining, machine learning, knowledge discovery in databases, pattern recognition, etc. Are these fields really different?
  • What is the most common data mining question you have heard?
  • Imagine that I can give you any data set by tomorrow. What kind of data would you like mining?
  • And more

Interview by Vincent Granville on AnalyticBridge

  • Which analytical fields are likely to experience growth, and why?
  • Which methodologies might become obsolete, which ones are likely to entertain growth?
  • What do you recommend for students starting an analytical career or choosing a University curriculum?
  • What are the biggest successes of data mining and statistical sciences in the corporate world?
  • What are the best practices for analytic professionals?
  • And more

Interview by Lars Johansson on WebAnalysts.Info

  • What is your definition of predictive analytics?
  • And more

Interview by Gary Angel on SemAngel

  • Why do you think analytics - especially advanced analytics – has proven challenging for many industries to really embed?
  • Do you sometimes find yourself surprised at the low-level of analytic sophistication in even very big organizations with very large marketing budgets?
  • And more