Big data analytics: Academic perspectives

Muhammad D. Abdulrahman, Nachiappan Subramanian, Hing Kai Chan, Kun Ning

Research output: Chapter in Book/Conference proceedingBook Chapterpeer-review

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.

Original languageEnglish
Title of host publicationSupply Chain Management in the Big Data Era
PublisherIGI Global
Pages1-12
Number of pages12
ISBN (Electronic)9781522509578
ISBN (Print)9781522509561
DOIs
Publication statusPublished - 4 Nov 2016

ASJC Scopus subject areas

  • Business, Management and Accounting (all)
  • Computer Science (all)
  • Economics, Econometrics and Finance (all)

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