Data Mining and Statistics: Tools for Decision Making in the Age of Big Data

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Author(s): Hirak Dasgupta (Symbiosis Institute of Management Studies, India)
Copyright: 2017
Pages: 19
Source title: Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence
Source Author(s)/Editor(s): Shrawan Kumar Trivedi (BML Munjal University, India), Shubhamoy Dey (Indian Institute of Management, Indore, India), Anil Kumar (BML Munjal University, India)and Tapan Kumar Panda (Jindal Global Business School, India)
DOI: 10.4018/978-1-5225-2031-3.ch002

Keywords: Business & Management / Business Information Systems / Business Intelligence / Business Science Reference

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Abstract

In the age of information, the world abounds with data. In order to obtain an intelligent appreciation of current developments, we need to absorb and interpret substantial amounts of data. The amount of data collected has grown at a phenomenal rate over the past few years. The computer age has given us both the power to rapidly process, summarize and analyse data and the encouragement to produce and store more data. The aim of data mining is to make sense of large amounts of mostly unsupervised data, in some domain. Data Mining is used to discover the patterns and relationships in data, with an emphasis on large observational data bases. This chapter aims to compare the approaches and conclude that Statisticians and Data miners can profit by studying each other's methods by using the combination of methods judiciously. The chapter also attempts to discuss data cleaning techniques involved in data mining.

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Data Mining and Statistics: Tools for Decision Making in the Age of Big Data

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