Summary - Java Data Mining: Strategy, Standard, and Practice - page 463

Chapter
19
Summary
Every end is a new beginning.
—Proverb
Data mining is a journey, one where the arrival at insights and
discoveries is the launching point for further inquiry—a new begin-
ning. Having read this, and possibly other, topics on data mining,
you too are ready for a new beginning in applying data mining to
your business or domain.
This topic began by exploring data mining in the context of an
overall strategy. Data mining was framed as a key strategic compo-
nent for solving important business problems and the role of stan-
dards that support such a strategy was explored. As a technology,
data mining is fascinating for what it can accomplish, the knowledge
it can extract, and the speed at which it can extract it. However, tech-
nology for technology's sake is not sufficient—it must be put to use
to solve practical and real business and scientific problems.
Part I highlighted general business (or cross-industry) problems,
as well as problems specific to several industries to which data min-
ing can be applied. The data mining process was examined in the
context of another standard, CRISP-DM. Such a process helps to
define data mining-related business problems with clear goals; as a
result, higher quality results can be achieved. The various mining
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