Assessment on Progression, Techniques of Data Mining and Its Applications

Abstract

Data mining is the process of analyzing data from different views and summarizing it into useful data. “Data mining, also popularly referred to as knowledge discovery from data (KDD), is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams.”. This paper provides a survey on various data mining techniques such as classification, clustering, regression, summarization and so on. This paper also discusses some of the data mining applications, additionally gift data processing primitives, from that data processing question languages will be designed. Problems concerning a way to integrate an information mining system with a database or data warehouse are mentioned. Additionally to finding out a classification of information mining systems, and its difficult analysis problems for building data processing tools of the long run.