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2011 Data Miner Survey:
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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.
We have conducted the Data Miner Survey annually since 2007. Highlights for each
year are available online. Contact us to receive the full summary reports (FREE).
After the 2011 survey, we moved to a bi-annual schedule. The 2013 Data Miner
Survey was launched in January 2013.
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.
We have conducted the Data Miner Survey annually since 2007. Highlights for each
year are available online. Contact us to receive the full summary reports (FREE).
- 2007 Highlights
- 2008 Highlights
- 2009 Highlights
- 2010 Highlights -- Including best practices data miners shared for overcoming
the top challenges data miners face.
After the 2011 survey, we moved to a bi-annual schedule. The 2013 Data Miner
Survey was launched in January 2013.
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.
- TOOLS: R continued its rise this year and is now being used by close to half
of all data miners (47%). R users report preferring it for being free, open
source, and having a wide variety of algorithms. Many people also cited R's
flexibility and the strength of the user community. In the 2011 survey we
asked R users to tell us more about their use of R. Read the R user
comments about why these use R (pros), the cons of using R, why they select
their R interface, and how they use R in conjuction with other tools.
STATISTICA is selected as the primary data mining tool by the most data
miners (17%). Data miners report using an average of 4 software tools
overall. STATISTICA, KNIME, Rapid Miner and Salford Systems received the
strongest satisfaction ratings in 2011.
- 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.
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