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).
Definitions of data mining
abound, and they vary among practitioners.
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.
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
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.