 Successful Data Mining |
Data mining is a powerful technology for exploiting data. We use the term to refer to data exploitation in general, particularly using advanced algorithms such as neural networks, decision trees, clustering, and link analysis. Two different markets are emerging for data mining software. The first is the market for tools that implement advanced algorithms for knowledgeable users. The users understand data analysis, and often have a background in statistics, mathematics, or the sciences. Typically, a small data mining group specializes in the analysis and returns the results to the rest of the organization.
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Data mining is the search for actionable patterns in data. Actionable patterns are those that have a measurable effect on the business. Data mining is particularly useful as a part of customer relationship management determining the right message to get to the right customer at the right time. A simple example illustrates the importance of analyzing data to understand customer behavior. For instance, a cellular company was surprised to learn that the best and most profitable customers disproportionately made complaints to their customer service center. Far from being a nuisance or a cost center, the service center is an important conduit to the most important segment of the customer base.
The second market is the integrating of algorithms into applications. Data mining algorithms are incorporated into tools used by end-users. Far from being PhDs, the ultimate users may be customer service reps (CSRs) whose script depends on an underlying analysis of complex behavioral patterns. Some companies, such as HNC, incorporate their own software. Others integrate tools software, such as ValEX from Exchange Applications that integrate with SAS Institute's Enterprise Miner. More information about SAS Institute can be found at http://www.sas.com
Regardless of how you use data mining, it is worth asking the question, how can you use data mining successfully. A typical introduction to data mining is through an engagement using your data to inform you about your business. A product integrated into a new application does not provide a customized analysis that may be needed for your business. However, such a product is likely to perform that application very well.
The successful data mining engagement requires:
Business Needs - what part of the organization is using data mining, what are the drivers, both strategic and tactical.
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