Data mining is the process of extracting patterns from data by combining techniques from machine learning, statistics, and data processing technologies in an organization.
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning (ML), statistics, and database systems. Furthermore, data mining is an interdisciplinary sub-field of computer science and statistics with an overall goal to extract information with intelligent methods from a data set and transform that information into a comprehensible structure for further use. Besides, data mining is the analysis step of the knowledge discovery in databases (KDD) process.
Data mining is the way programs discover patterns in large data sets with various formats such as text and multimedia. Besides, data mining is the cross-section between computer science and statistics with the goal of extracting information and transforming the information into an understandable structure for further use or processing. And it is a technique employed to describe collection, extracting, warehousing, analysis and statistics of data in a given environment.
There are two types of data mining, namely predictive analysis and descriptive analysis.
- Predictive data mining analysis: Predictive analysis is used to describe the analytics performed on a data set to make predictions about future events.
- Descriptive data mining analysis: Descriptive analysis provides descriptive information from the data set based on classification, association and feature extraction in order to report the previous behavior of the data.