As a service to the data mining community, RexerAnalytics conducts an annual online survey (started in 2009). It analyzes some factors like experiences, priorities, views and challenges being faced by data mining industry. The Third Annual Data Miner Survey results were announced after studying the reports of 710 respondents from the data mining community. It was concluded that data miners and their organization’s are highly confident and happy with their services and analytic capabilities giving a feedback of “above average” or “excellent” performances. Most of them even assured that economy conditions will never be a set back or a weak point for them. According to the survey result, the most commonly used and most satisfying primary data mining tools this year are IBM SPSS Modeler (SPSS Clementine), Statistica, and IBM SPSS Statistics (SPSS Statistics). Open source tool Weka is increasingly used by both academic and for-profit data miners. SAS Enterprise Miner dropped in data miner’s tool rankings this year.
Some 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.
- 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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