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Automatic Control and Information Sciences. 2017, 3(1), 8-15
DOI: 10.12691/acis-3-1-3
Open AccessReview Article

Heterogeneous Data and Big Data Analytics

Lidong Wang1,

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

Pub. Date: June 15, 2017
View Full Text Full Text PDF (347 KB) Full Text ePUB(82 KB)

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

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.

Keywords:
Big Data Big Data analytics heterogeneous data deep learning data mining machine learning heterogeneous computing computational intelligence artificial intelligence

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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