710 analytic professionals from 58 countries participated in the 2009 survey.
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- ALGORITHMS: As in previous years, data miners’ most commonly used algorithms are regression, decision trees, and cluster analysis.
- ORGANIZATIONAL IMPORTANCE: 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.
- IMPACT OF ECONOMY: Most data miners feel that the economy will not negatively impact them.
- CHALLENGES: 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.
- TOOLS: 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. Users of IBM SPSS Modeler, Statistica, and Rapid Miner are the most satisfied with their software.
The full summary report includes additional material about algorithms and software usage, the fields applying analytics, corporate analytic capabilities, analytic challenges, concerns, analytic success measurement, and more.