1. Decision Support Technology

2. Directed Classification and Prediction

3. Undirected Association, Clustering, and Recognition.

The first technical aspect of data mining is decision support technology. Decision support covers the entire information infrastructure system that companies use to make informed customer decisions. It’s based on recognized data patterns. Data mining helps, identify those patterns.

Data Warehousing: A data warehouse is a database that stores information from a variety of operational systems. It allows companies to view information as a single entity rather than as a collection of information bits.

Online Analytical Processing: OLAP databases are often speedier and more clearly organized than data warehouses, OLAP databases organize information along specified variables and allow for more precise analysis of the information they contain.

Integration of Decision Support: Facts churned out by databases and mainframe computers don’t always create a vivid enough picture to create solutions. Decision support technology is a collection of software and hardware that allows you to visualize the information gained through data mining.

In data mining, you use data to build a model demonstrating how every record in your customer database can be categorized based on any combination of variables. This method is the second technical aspect of data mining: classification is the method of categorizing record in a database by predefined criteria – for e.g. assigning customers to specific purchasing categories. Prediction is taking the mined customer information, analyzing it, and predicting how customers may react in the future.

Undirected data mining is an automated process in which similarities among all records in a database of customer records are found. The third technical aspect of data mining is undirected association, clustering, and recognition. Some technical aspects of determining are directed classification and prediction, undirected recognition and clustering, and data warehousing and OLAP. In directed data mining, you use data to build a model demonstrating how every record in your customer database can be categorized, based on any combination of variables.