Presenting a Best Practices Framework for Data Mining June 2013

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    I copresented (with Artus Krohn-Grimberghe) a session called “A Best Practices Framework for Data Mining” for the June 13, 2013 PASS Virtual Business Analytics Group.  This talk marks my third for this relatively new group, and I’m glad to work with leader Melissa Demsak on these quality presentations.  For this talk, we had about 40 people, and seamlessly delivered the talk from both North America (myself) and Europe (Artus, who is in Germany).  This post has the details and the links to the slides and recorded presentation.


    Abstract (as shared on the PASS website):

    Data mining increasingly fascinates business people and information technology professionals alike, with the promise of finding meaningful patterns, relationships, and opportunities in our continuously growing volumes of data. There are tried and tested best practices you can follow to begin and improve your data mining efforts.

    Our purpose in this presentation was to share some of the highlights of our longer one-day preconference session by a similar title “A Best Practices Cookbook for Data Mining”.  Artus and I recently delivered this session for the PASS Business Analytics Conference in April 2013.  We are hoping to share this material (updated as new innovations in machine learning and data mining occur) at other conferences.

    Artus and I hope to be presenting other sessions for PASS conferences beyond just this talk, and we are open to your suggestions and comments for new material.  Having each been university professors in this area, each of us has a lot of potential material.  We hope to share forward our years of formal instruction and practical business experience, based on working with university students and peer industry professionals.


    Link to Slides:

    Link to Recorded WMV Presentation:

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