Data mining is the process of discovering interesting patterns and knowledge from large amounts of data. In the industry, the term data mining is often used to refer to the knowledge discovery process. Many people treat data mining as a synonym for knowledge discovery process and many others view data mining as a step in the process of knowledge discovery.
Typical steps involved in the knowledge discovery process is as follows
- Data Cleaning – Removing noise and inconsistent data
- Data Integration – Combine data from multiple data sources
- Data Selection – Filter and retrieve data that is relevant for the analysis task
- Data Transformation – Consolidate and transform the selected data to a form appropriate for data mining
- Data Mining – Apply intelligent methods to extract patterns and trends
- Pattern Evaluation – Identify truly interesting patterns of knowledge
- Knowledge presentation – Present mined knowledge to users using visualization and presentation techniques.
Examples for Data Mining:
Data mining systems can analyze customer data and predict the credit risk of new customers based on their income, age, and previous credit information.