How does someone purchase an intangible, cryptic, seemingly immeasurable technology? Beyond the inherent up-front risks of engaging in what is essentially a discovery process, just identifying a starting point can be intimidating and mystifying. Despite its elusive nature, data mining technology has surpassed the flash-in-the-pan "miracle tool" stigma with widespread and sustained success stories highlighted in mainstream publications, along with recurring case studies of improved operational efficiencies, enhanced business intelligence and residual payback. For any organization with annual revenues more than $50 million, employing data mining technology is not a matter of whether, but when.
Data mining has been seeping into mainstream business applications for more than two decades. Numerous case studies may be quickly referenced via a simple Internet or publication search. Its progress is unstoppable, propelled by sustained value justifications- yet stinted by the complexities of development, interpretation, integration and adoption. This article will suggest how to properly approach the starting line and how to implement a purposefully flexible framework for establishing an efficient and effective organizational data mining process.
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