eng Science and Education Publishing Automatic Control and Information Sciences 2375-1630 2017-10-27 3 1 8 15 10.12691/acis-3-1-3 ACIS2017313 article Lidong Wang lwang22@students.tntech.edu 1 Department of Engineering Technology, Mississippi Valley State University, Itta Bena, MS, USA 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. http://pubs.sciepub.com/acis/3/1/3/acis-3-1-3.pdf Big Data Big Data analytics heterogeneous data deep learning data mining machine learning heterogeneous computing computational intelligence artificial intelligence