Copyright (c) 2013 Rexer Analytics All Rights Reserved
2011 Data Miner Survey:
2011 Data Miner Survey:  

Thank you for your interest in the 5th Annual Rexer Analytics Data Miner Survey.  

This research program examines the analytic behaviors, needs, preferences, and
views of data mining professionals.  It is conducted as a service to the data mining
community.  It s not conducted for, or sponsored by, any third party.  Rexer Analytics
is committed to freely disseminating our research findings through report
summaries, conference presentations, and personal contact.  If you would like a
copy of this year's FREE 37 page summary report, or summary reports from
previous years, please contact us at
DataMinerSurvey@RexerAnalytics.com.  
Please also contact us if you have questions about this research program or if you
have suggestions for topics to be included in future Data Miner Surveys.























































Rexer Analytics has been conducting the Data Miner Survey since 2007.  Summary
reports (PDFs of about 40 pages) of each of the six surveys are available FREE to
everyone -- simply email your request to
DataMinerSurvey@RexerAnalytics.com.  
Also, highlights of each Data Miner Survey are available online, including best
practices shared by respondents on analytic success measurement, overcoming
data mining challenges, and other topics.

                 overcoming the top data mining challenges   
 
2011 SURVEY HIGHLIGHTS:

  • SURVEY & PARTICIPANTS:  52-item survey of data miners, conducted on-
    line in 2011.  Participants: 1,319 data miners from over 60 countries.

  • FIELDS & GOALS:  Data miners work in a diverse set of fields.  CRM /
    Marketing has been the #1 field in each of the past five years.  Fittingly,
    “improving the understanding of customers”, “retaining customers” and other
    CRM goals continue to be the goals identified by the most data miners.

  • ALGORITHMS:  Decision trees, regression, and cluster analysis continue to
    form a triad of core algorithms for most data miners.  However, a wide variety
    of algorithms are being used.   A third of data miners currently use text mining
    and another third plan to in the future.  Text mining is most often used to
    analyze customer surveys and blogs/social media.


  • TECHNOLOGY:  Data Mining most often occurs on a desktop or laptop
    computer, and frequently the data is stored locally.  Model scoring typically
    happens using the same software used to develop models.

  • VISUALIZATION:  Data miners frequently use data visualization techniques.  
    More than four in five use them to explain results to others.  MS Office is the
    most often used tool for data visualization.  Extensive use of data visualization
    is less prevalent in the Asia-Pacific region than other parts of the world.

  • ANALYTIC CAPABILITY & SUCCESS:  Only 12% of corporate respondents
    rate their company as having very high analytic sophistication.  However,
    companies with better analytic capabilities are outperforming their peers.  
    Respondents report analyzing analytic success via Return on Investment
    (ROI), and analyzing the predictive validity or accuracy of their models.  
    Challenges to measuring analytic success include client or user cooperation
    and data availability / quality.  Read the best practices data miners shared    
    for measuring analytic success.  

  • FUTURE:  Data miners are optimistic about continued growth in data mining
    adoption and the positive impact data mining will have.  As in previous years,
    data miners see growth in the number of projects they will be conducting.  
    And growth in data mining adoption is the number one “future trend”
    identified.  Participants pointed out that care must be taken to protect privacy
    when conducting data mining.  Data miners also shared many examples of
    the positive impact they feel data mining can have to benefit society.  Health /
    medical advances was the area of positive impact identified by the most data
    miners.  Read the full list of positive impact examples identified by data    
    miners in the 2011 survey.  
Over 4,000 people have requested
recent Summary Reports.

People have written about or cited
this research in 13 languages.