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Big Data Analytics: Academic Perspectives

Big Data Analytics: Academic Perspectives

Muhammad D. Abdulrahman, Nachiappan Subramanian, Hing Kai Chan, Kun Ning
Copyright: © 2017 |Pages: 12
ISBN13: 9781522509561|ISBN10: 1522509569|EISBN13: 9781522509578
DOI: 10.4018/978-1-5225-0956-1.ch001
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MLA

Abdulrahman, Muhammad D., et al. "Big Data Analytics: Academic Perspectives." Supply Chain Management in the Big Data Era, edited by Hing Kai Chan, et al., IGI Global, 2017, pp. 1-12. https://doi.org/10.4018/978-1-5225-0956-1.ch001

APA

Abdulrahman, M. D., Subramanian, N., Chan, H. K., & Ning, K. (2017). Big Data Analytics: Academic Perspectives. In H. Chan, N. Subramanian, & M. Abdulrahman (Eds.), Supply Chain Management in the Big Data Era (pp. 1-12). IGI Global. https://doi.org/10.4018/978-1-5225-0956-1.ch001

Chicago

Abdulrahman, Muhammad D., et al. "Big Data Analytics: Academic Perspectives." In Supply Chain Management in the Big Data Era, edited by Hing Kai Chan, Nachiappan Subramanian, and Muhammad Dan-Asabe Abdulrahman, 1-12. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0956-1.ch001

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Abstract

This chapter discusses the scholarly views on big data analytics with respect to the challenges in terms of visualization and data driven research in smart cities and ports. The prominent challenges and emerging research on structuring data, data mining algorithms and visualization aspects are shared by academic experts based on their ongoing research experience. Scholars agreed that being able to analyze huge data at once is highly critical for the embracement and success of big data research and the utilization of its findings particularly for entities with highly dynamic and complex demands such as cities and ports. It was noted that developing robust ways of handling and clean qualitative social media data as well as getting well-trained and highly skilled human resources in all aspects of big data analysis and interpretation remains a major challenge.

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