Essential Guide

Guide to big data analytics tools, trends and best practices

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data mining

Data mining is the analysis of data for relationships that have not previously been discovered. For example, the sales records for a particular brand of tennis racket might, if sufficiently analyzed and related to other market data, reveal a seasonal...

Data mining is sorting through data to identify patterns and establish relationships.

Data mining parameters include:

  • Association - looking for patterns where one event is connected to another event
  • Sequence or path analysis - looking for patterns where one event leads to another later event
  • Classification - looking for new patterns (May result in a change in the way the data is organized but that's ok)
  • Clustering - finding and visually documenting groups of facts not previously known
  • Forecasting - discovering patterns in data that can lead to reasonable predictions about the future (This area of data mining is known as predictive analytics.)

Data mining techniques are used in a many research areas, including mathematics, cybernetics, genetics and marketing. Web mining, a type of data mining used in customer relationship management (CRM), takes advantage of the huge amount of information gathered by a Web site to look for patterns in user behavior.

This was first published in December 2008

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Essential Guide

Guide to big data analytics tools, trends and best practices

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