International Journal of Computer Science Trends and Technology (IJCST) – Volume 2 Issue 3, May-Jun 2014 ISSN: 2347-8578 www.ijcstjournal.org Page 78 A Survey of Data Mining: Concepts with Applications and its Future Scope Dr. Zubair Khan 1 , Ashish Kumar 2 , Sunny Kumar 3 M.Tech Research Scholar 2 . Department of Computer Science and Engineering 1 Invertis University Bareilly, 243123 Uttar Pradesh - India ABSTRACT In this paper we have to focus on data mining concept and its tools and technology which help us for market perspective to take a proper decision and get a proper result. Data mining is a logical process that is used to analyze large amounts of information that can be in the form of document in order to find important data. The goal of data mining is to find patterns that were previously unknown. Once you have found out those patterns, you can use them to solve number of complex problems. Data mining [sometimes called data or knowledge discovery from data (KDD)] is the process of analyzing data from huge amount of data and summarizing it into useful information. Data mining is one of a number of analytical tools for analyzing data. It allows users to search and analyze data from many different source and transform into decision making data from which user can take decision. IT is the process of finding patterns among dozens of fields in large relational databases. Data mining is a powerful tool because it can provide relevant information. But it is not so easy to get relevant information that can help you to take proper decision. This is where data mining becomes a powerful tool that will help to extract useful information. Keywords:- Data Mining, KDD, Data Mining Task, Data Preprocessing, Visualization of the data mining model, Data Mining: classification, methods and its application I. INTRODUCTION The primary aim of data mining is to extract the useful information for users from a large amount of data. As the data are available in the different formats such as graphically, audio, video or in the form of varies documents so that the proper action to be taken [1]. Not only to search or analyse these data but also take a good and proper decision for business perspective. When the user will required the data should be retrieved from the database and make the better decision. There is huge amount of complex data but we hardly able to transform them in to useful information and knowledge for managerial decision making for business. To generate useful information it requires massive collection of integrated data. It may be different formats like graphical, audio/video, text, numbers figures, and Hypertext formats. To take complete advantage of large data; the data retrieval from large database is simply not enough for proper decision, it requires a tool for automatic summarization of data, extraction from information stored, and the discovery of patterns in database. With the huge amount of data stored in files, databases, and other repositories system, it is important for that, to develop powerful tool for analysis and extracting the useful of such data or knowledge that could help in decision- making. The only answer to all above these is ‘Data Mining’. It is the process of extraction hidden predictive information from large databases; it is a powerful tool and technology with great potential to help organizations focus on the most important information in large data sets. Data mining tools predict future growth and its behaviours. II. STEPS OF DATA MINING In general people feel helpless for analysed the large amount of data sets. Data mining can find the useful information that will help to users according to their needs for business perspective to take the proper decision. Data mining is the process of knowledge discovery [2]. KDD as a process is depicted in Figure 1 [8] and consists of an iterative sequence of the following steps: RESEARCH ARTICLE OPEN ACCESS