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2009 Data Miner Survey:
2009 Data Miner Survey:
Thank you for your interest in the Third Annual Rexer Analytics Data Miner Survey.
This research examined the analytic behaviors, needs, preferences, and views of
data mining professionals. It was conducted as a service to the data mining
community. It was 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 our FREE 48 page summary report, please contact Karl Rexer at
krexer@RexerAnalytics.com.
The Fourth Annual Data Miner Survey was launched in the Spring of 2010.
Thank you for your interest in the Third Annual Rexer Analytics Data Miner Survey.
This research examined the analytic behaviors, needs, preferences, and views of
data mining professionals. It was conducted as a service to the data mining
community. It was 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 our FREE 48 page summary report, please contact Karl Rexer at
krexer@RexerAnalytics.com.
The Fourth Annual Data Miner Survey was launched in the Spring of 2010.
2009 SURVEY HIGHLIGHTS:
- 40-item survey of data miners, conducted on-line in early 2009.
- 710 participants from 58 countries.
- Data miners’ most commonly used algorithms are regression, decision trees,
and cluster analysis.
- Data mining is playing an important role in organizations.
- Half of data miners say their results are helping to drive strategic
decisions and operational processes.
- 58% say they are adding to the knowledge base in the field.
- 60% of respondents say the results of their modeling are deployed
always or most of the time.
- Most data miners feel that the economy will not negatively impact them.
- Almost half of industry data miners rate the analytic capabilities of their
company as above average or excellent. But 19% feel their company has
minimal or no analytic capabilities.
- The top challenges facing data miners are dirty data, explaining data mining
to others, and difficult access to data. However, in 2009 fewer data miners
listed data quality and data access as challenges than in the previous year.
- IBM SPSS Modeler (SPSS Clementine), Statistica, and IBM SPSS Statistics
(SPSS Statistics) are identified as the “primary tools” used by the most data
miners.
- Open-source tools Weka and R made substantial movement up data
miner’s tool rankings this year, and are now used by large numbers of
both academic and for-profit data miners.
- SAS Enterprise Miner dropped in data miner’s tool rankings this year.
- Users of IBM SPSS Modeler, Statistica, and Rapid Miner are the most
satisfied with their software.
- Fields & Industries: Data mining is everywhere. The most sited areas are
CRM / Marketing, Academic, Financial Services, & IT / Telecom. And in the
for-profit sector, the departments data miners most frequently work in are
Marketing & Sales and Research & Development.
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