International Journal of Management, IT & Engineering Vol. 8 Issue 9(1), September 2018, ISSN: 2249-0558 Impact Factor: 7.119 Journal Homepage: http://www.ijmra.us, Email:
[email protected] Double-Blind Peer Reviewed Refereed Open Access International Journal - Included in the International Serial Directories Indexed & Listed at: Ulrich's Periodicals Directory ©, U.S.A., Open J-Gage as well as in Cabell’s Directories of Publishing Opportunities, U.S.A Data Mining: Architecture, Techniques and its uses ANJU DEVI Abstract Data Mining refers to extracting useful information or knowledge from large amount of data. It is beneficial in every field like business, medicine, education sectors, health care, industrial, management, engineering, web data, banking, customer relationship management, fraud detection etc. It is also known as knowledge discovery process. Data mining is an integral part of Knowledge Discovery in Database (KDD). In this paper different types, architecture of data mining are describe in details with the help of block diagram. Its techniques also define which are summarization, classification, association rules, prediction, clustering and regression etc. Keywords: Data mining, Architecture, Aspects, Techniques and uses Introduction of Data Mining Data mining is a field of research which are very popular today. A large amount of data is available in every field of life such as: banking, medicine, insurance, education sectors etc. due to advances of digitization techniques. Data mining is a process of selecting interested pattern to from a large amount of data or information. Data Mining is similar to Data science. It is an interdisciplinary turf about scientific methods, process, and system to take out knowledge from data in various forms.