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2013 Data Miner Survey:
2013 Data Miner Survey:  

Thank you for your interest in the 6th Rexer Analytics Data Miner Survey.  

This research program examines the analytic behaviors, views and preferences of
data mining, data science and analytic professionals.  

To receive a copy of the FREE 41-page 2013 Data Miner Survey summary report,
please contact us at

We deeply thank everyone who completed this year's Data Miner Survey -- 1,259
people!  We also appreciate the efforts of everyone who contributed questions and
suggestions that have improved this research program.  Thank you.  This is a
collaborative project, and is not being conducted for any third party.  Please email
us if you have any 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  
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.

           -- Verbatims:  The Positive Impact of Data Mining  
           -- Verbatims:  
Analytic Success Measurement - Best Practices  
           -- Verbatims:  
Insights from R Users  

           -- Verbatims:  Overcoming Top Data Mining Challenges - Best Practices


  • SURVEY & PARTICIPANTS:  68-item survey conducted online in 2013.  
    Participants: 1,259 analytic professionals from 75 countries.

  • FOCUS ON CRM:  In the past few years, there has been an increase among
    data miners in the already substantial area of customer-focused analytics.  
    Respondents are looking for a better understanding of customers and
    seeking to improve the customer experience.  This can be seen in their goals,
    analyses, big data endeavors, and in the focus of their text mining.

  • BIG DATA:  Many in the field are talking about the phenomena of Big Data.  
    There are clearly some areas in which the volume and sources of data have
    grown.  However it is unclear how much Big Data has impacted the typical
    data miner.  While data miners believe that the size of their datasets have
    increased over the past year, data from previous surveys indicate that the
    size of datasets have been fairly consistent over time.

  • THE ASCENDANCE OF R:  The proportion of data miners using R is rapidly
    growing, and since 2010, R has been the most-used data mining tool.  While
    R is frequently used along with other tools, an increasing number of data
    miners also select R as their primary tool.

  • CHALLENGES IN THE USE OF ANALYTICS:  Data miners continue to report
    challenges at each level of the analytic process.  Companies often are not
    using analytics to their fullest and have continuing issues in the areas of
    deployment and performance measurement.

  • ENGAGEMENT & JOB SATISFACTION:  The Data Miners in our survey are
    highly engaged with the analytic community: consuming and producing
    content, entering competitions and searching for education and growth within
    their jobs.  All of these activities lead to high job satisfaction, which has been
    increasing over time.

  • ANALYTIC SOFTWARE:  Data miners are a diverse group who are looking
    for different things from their data mining tools.  Ease-of-use and cost are two
    distinguishing dimensions.  Software packages vary in their strengths and
    features.  STATISTICA, KNIME, SAS JMP and IBM SPSS Modeler all receive
    high satisfaction ratings.

  • OTHER FINDINGS include the labels analytic professionals use to describe
    themselves (Data Scientist is #1), the algorithms being used (regression,
    decision trees, and cluster analysis continue to be the triad of core
    algorithms), and computing environments (cloud computing is increasing).
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