HIGHLIGHTS from the 3rd Annual Data Miner Survey:
- 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.
Additional Info can be taken from the Rexer Analytics website- I find their annual survey one of the most useful in summarizing the entire DM and A landscape.