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Data B. Transport: Understanding and assessing options. Corporate Partnership Board Report, the Organization for Economic Cooperation and Development (OECD)/International Transport Forum, May 2015, 1-66.

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Article

Heterogeneous Data and Big Data Analytics

1Department of Engineering Technology, Mississippi Valley State University, Itta Bena, MS, USA


Automatic Control and Information Sciences. 2017, Vol. 3 No. 1, 8-15
DOI: 10.12691/acis-3-1-3
Copyright © 2017 Science and Education Publishing

Cite this paper:
Lidong Wang. Heterogeneous Data and Big Data Analytics. Automatic Control and Information Sciences. 2017; 3(1):8-15. doi: 10.12691/acis-3-1-3.

Correspondence to: Lidong  Wang, Department of Engineering Technology, Mississippi Valley State University, Itta Bena, MS, USA. Email: lwang22@students.tntech.edu

Abstract

Heterogeneity is one of major features of big data and heterogeneous data result in problems in data integration and Big Data analytics. This paper introduces data processing methods for heterogeneous data and Big Data analytics, Big Data tools, some traditional data mining (DM) and machine learning (ML) methods. Deep learning and its potential in Big Data analytics are analysed. The benefits of the confluences among Big Data analytics, deep learning, high performance computing (HPC), and heterogeneous computing are presented. Challenges of dealing with heterogeneous data and Big Data analytics are also discussed.

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