What Are Different Data Mining Primitives?

1. Task Relevant Data
a. Database or data warehouse name
b. Database tables or data warehouse cubes
c. Condition for data selection
d. Relevant attributes or dimensions
e. Data grouping criteria
2. Type of knowledge to be mined
a. Characterization
b. Discrimination
c. Association
d. Classification/prediction
e. Clustering
f. Outlier Analysis
g. Other data mining tasks
3. Background Knowledge
a. Typical background knowledge: Concept hierarchies
b. Schema Hierarchy
c. Set-grouping hierarchy
d. Operation-derived hierarchy
e. Rule based hierarchy
4. Pattern interestingness measurements
a. Simplicity
b. Certainty
c. Utility
d. Novelty
5. Visualization/presentation of discovered patterns
a. Different backgrounds/usages may require different forms of representation e.g. Rules, tables
b. Importance of concept hierarchy
c. Different kind of knowledge require different representation: Association, classification, clustering etc

Data Mining basically refers to the retrieving and extration of important information from a data base or a huge set of data. There are a number of techniques for data mining depending on what is it used for such as predictive data mining, Bagging, Boosting etc. To know about them in detail, see the link below:
www.statsoft.com