Originally, ‘data mining’ or ‘data dredging’ was a derogatory term referring to attempts to extract information that was not supported by the data. However now, it is an underlying distribution from which the visible data is drawn.
It is fundamentally an applied discipline and requires an understanding of both statistical and computational issues.
The huge potential for identifying hidden knowledge in huge data volumes is a pitfall. Hugh data volumes potentially contain much information, and not all of this information is necessary to solve a given business question.
Organizations who want to excel at using their data to improve their business do not view data mining as a sideshow.
Instead, their business strategy must include collecting data, analyzing data for long term benefit and acting in the results.
Data mining
