Data Mining


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Data Mining

The practice of looking for a pattern in a large amount of seemingly random data. Data mining is usually done with a computer program and helps in marketing. That is, a company can look at the (publicly available) purchase patterns of a person or group of persons and determine what products to direct at them.
References in periodicals archive ?
Data mining is the process of data analysis that results in discovery of implicit, but potentially useful information as well as previously unknown patterns and relationships, which are hidden in data (Witten, Frank 2005).
The organization-level driver to support the investment in a data warehouse and in data mining tools is that these investments identify value-adding business processes.
Data mining offers law enforcement agencies potential benefits in the area of tactical crime analysis.
explained that NAG Data Mining Components were developed in response to requests by various commercial companies and researchers now using data mining techniques to make better use of the vast and growing datasets that are now commonplace.
As a method to improve the sharing and storing of client information in data warehouses, data mining is now beginning to make advances into these systems.
Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more
But the head of the agency would still have to certify in writing that the data mining was necessary and appropriate for a lawful purpose.
Users build a map of their data mining project--called a "stream"--by selecting icons--called "nodes"--that represent steps in the process.
One of the nice things about today's data mining tools is you don't need a computer science degree to use them effectively," says Pelletier.
First released in 1994, Clementine is SPSS' industry-leading data mining workbench.
Based on the popular Weka open source data mining project, Pentaho Data Mining uses advanced analytic algorithms and techniques to uncover hidden patterns and opportunities within large volumes of data.