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.
IBM SPSS predictive analytics tools for big data may be the best option for your enterprise. KNIME open source data analytics delivers commercial extensions for big data, cluster operations and collaboration.
SAP Predictive Analytics software is comprised of Automated Analytics and Expert Analytics. Learn how these products could be essential for your enterprise.