A Survey of Data Mining Techniques and Tools

Abstract: Data mining is the process of extracting the useful data, patterns and trends from a large amount of data by using techniques like clustering, classification, association and regression. Data mining techniques are used for information retrieval, statistical modelling and Machine learning. These techniques employ data pre-processing, data analysis and data interpretation. There are a wide variety of applications in real life. 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. Various tools are available which supports different algorithms. A summary about data mining tools available and the supporting algorithms is the objective of this paper. Comparison between various tools has also been done to enable the users use various tools according to their requirements and applications.

Keywords: Data mining, Clustering, Classification, Association and Regression.