Data mining is the method of searching of data to discover patterns and trends that go beyond simple analysis. Another name of data mining is Knowledge Discovery in Data (KDD). Data mining is a process used by companies for sorting the large data sets in order to identify the patterns and establish strong relationships to solve the issues over data analysis. The strategies and tools of the data mining help the firms or the organizations to anticipate their future needs or requirements. The organizations can learn more about the demands and requirements of the customers by using the software to visualize the patterns in large batches. It is also important to note that the data mining depends on data collection, ware housing and computer processing.
In data mining, association rules are developed or build by examining the data for frequent then patterns, then using the support and confidence benchmark to search and find out the most important relationships within the data. The data mining parameters include Sequence or Path Analysis, Clustering, Classification and Forecasting. Sequence or Path Analysis parameters search for patterns where one event leads to another event. A Sequence is a list of sets of items in correct format or structure. A Classification parameter searches for new patterns and might result in a change in the manner or style the data is organized. Classification algorithms anticipate variables based on other factors within the database.
The techniques and methods of data mining are used in many important and different areas, including mathematics, research, cybernetics, genetics and marketing. Data mining can help the organizations to predict the behavior of the customers and with the use and help of predictive analysis can set itself in a much superior position from its competitors. Web mining which is a kind of data mining is used in customer relationship management. It is also used to integrate information gathered by traditional data mining tools, methods and techniques over the web.