Data Mining Techniques and Applications- A Review

Vol.6 No.3

Year: 2012

Issue: January-March

Title: Data Mining Techniques and Applications- A Review   

Author Name: Venkatesan Thillainayagam   

Synopsis:   

Data mining is the process of extracting patterns from data. Basically Data mining is the analysis of observational data sets to find unsuspected associations and to sum up the data in new ways that are both clear and useful to the data owner .It is seen as an increasingly important tool by modern business to transform data into business intelligence giving an informational advantage. The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. The review paper discusses few of the data mining techniques, algorithms and some of the organizations which have adapted data mining technology to improve their businesses and found excellent results. Data mining tools can answer business questions that traditionally were too time consuming to resolve. Data mining is becoming increasingly common in both the private and public sectors. Industries such as banking, insurance, medicine, and retailing commonly use data mining to reduce costs, enhance research, and increase sales. To be successful, data mining still requires skilled technical and analytical specialists who can structure the analysis and interpret the output that is created.