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Knowledge Discovery and Big Data Analytics: Issues, Challenges, and Opportunities

Knowledge Discovery and Big Data Analytics: Issues, Challenges, and Opportunities
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Author(s): Vinoth Kumar Jambulingam (VIT University, India) and V. Santhi (VIT University, India)
Copyright: 2017
Pages: 21
Source title: Web Semantics for Textual and Visual Information Retrieval
Source Author(s)/Editor(s): Aarti Singh (Guru Nanak Girls College, Yamuna Nagar, India), Nilanjan Dey (Techno India College of Technology, India), Amira S. Ashour (Tanta University, Egypt & Taif University, Saudi Arabia) and V. Santhi (VIT University, India)
DOI: 10.4018/978-1-5225-2483-0.ch007

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Abstract

The era of big data has come with the ability to process massive datasets from heterogeneous sources in real-time. But the conventional analytics can't be able to manage such a large amount of varied data. The main issue that is being asked is how to design a high-performance computing platform to effectively carry out analytics on big data and how to develop a right mining scheme to get useful insights from voluminous big data. Hence this chapter elaborates these challenges with a brief introduction on traditional data analytics followed by mining algorithms that are suitable for emerging big data analytics. Subsequently, other issues and future scope are also presented to enhance capabilities of big data.

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