What is Data Mining?
Data Mining is a class of applications that look for hidden patterns in a data. The applications can be used to identify related clusters of records, identify records that do not fit normal patterns, and can be used to predict future results. For example, data mining software can help retail companies find customers with common interests. The term is commonly misused to describe software that presents data in new ways. True data mining software doesn’t just change the presentation, but actually discovers previously unknown relationships among the data.
Data mining is usually defined as searching, analyzing and sifting through large amounts of data to find relationships, patterns, or any significant statistical correlations. With the advent of computers, large databases and the internet, it is easier than ever to collect millions, billions and even trillions of pieces of data that can then be systematically analyzed to help look for relationships and to seek solutions to difficult problems. Besides governmental uses, many marketers use data mining to find strong consumer patterns and relationships. Large organizations and educational institutions also data mine to find significant correlations that can enhance our society.
Data mining uses a relatively large amount of computing power operating on a large set of data to determine regularities and connections between data points. Algorithms that employ techniques from statistics, machine learning and pattern recognition are used to search large databases automatically. Data mining is also known as Knowledge-Discovery in Databases (KDD). Like the term artificial intelligence, data mining is an umbrella term that can be applied to a number of varying activities. In the corporate world, data mining is used most frequently to determine the direction of trends and predict the future. It is employed to build models and decision support systems that give people information they can use. Data mining takes a front-line role in the battle against terrorism. It was supposedly used to determine the leader of the 9/11 attacks. Data miners are statisticians who use techniques with names like near-neighbor models, k-means clustering, holdout method, k-fold cross validati
Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
Simply put, data mining is the process of exploring large quantities of data in order to discover meaningful information about the data, in the form of patterns and rules. In this process, various forms of analysis can be used to discern such patterns and rules in historical data for a given business scenario, and the information can then be stored as an abstract mathematical model of the historical data, referred to as a data mining model. After a data mining model is created, new data can be examined through the model to see if it fits a desired pattern or rule. From this information, actions can be taken to improve results in the given business scenario.
