A Tool for KDD: Data Mining

Abstract: With the rapid development of computer and information technology in the last decade, an enormous amount of data has been and will continuously be generated in massive scale. All the large MNC�s and organizations rely on database to manage their data and information. These databases are useful for conducting daily business transactions. Also, Data warehousing and data mining are essential elements of decision support, which has increasingly become a focus of database industry. This paper provides an overview of data warehousing and data mining, with an emphasis that how the data are analyzed to derive effective business strategies and discover better ways in carrying out business. This paper also describes various types of data warehousing and data mining methods. Also in this paper we did research on the top trends in data warehousing such as Hadoop, customer experience strategies to improve sales and service etc. We also described some examples and applications of data mining which we see in our day to day life like how data mining is used in Healthcare, data market basket, education system and social media. We described some of the current tools and techniques available at present for data warehousing in terms of the front end and backend tools. We further analyzed problems and issues and identified some of the research areas in the field of data warehousing.

Keywords: Data warehousing, Data Model, analysis, repository, KDD, logistics, Derived model.