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2007 Data Miner Survey:
2007 Data Miner Survey:
Thank you for your interest in the First Annual Rexer Analytics Data Miner Survey.
This research examined of the analytic behaviors, needs and preferences 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 7
page summary report, please contact Karl Rexer at krexer@RexerAnalytics.com.
Summaries of this research were presented at the October 2007 Oracle BIWA
Summit and the October 2007 SPSS Directions Conference.
The Second Annual Data Miner Survey was launched in January 2008. The results
of this follow-up research will be released mid-year.
Thank you for your interest in the First Annual Rexer Analytics Data Miner Survey.
This research examined of the analytic behaviors, needs and preferences 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 7
page summary report, please contact Karl Rexer at krexer@RexerAnalytics.com.
Summaries of this research were presented at the October 2007 Oracle BIWA
Summit and the October 2007 SPSS Directions Conference.
The Second Annual Data Miner Survey was launched in January 2008. The results
of this follow-up research will be released mid-year.
2007 HIGHLIGHTS:
- 27-item survey of data miners, conducted on-line in early 2007
- 314 responses from individuals in 35 countries
- Regression, decision trees and cluster analysis were the most commonly
used algorithms (mean number of algorithms used: 6.8)
- Top challenges data miners report are dirty data, data access, and explaining
data mining to others
- SPSS, SPSS Clementine, and SAS are the three most frequently utilized tools
(mean number of tools used: 4.5)
- There is increasing interest in the Oracle Data Mining tool, and decreasing
interest in C4.5/C5.0/See5
- The primary factors data miners consider when selecting an analytic tool are:
1) the dependability and stability of software, 2) the ability to handle large
data sets, and 3) data manipulation capabilities
- The findings vary somewhat depending on the domain in which the data
miner works, the tools used, geography, and several other dimensions
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