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Descriptive analytics methods in big data: a systematic literature review

In: Handbook of Big Data Research Methods

Author

Listed:
  • Nilupulee Liyanagamage
  • Mario Fernando

Abstract

The era of Big Data has received much attention due to its ability to transform business operations and innovation for modern society. Despite the trends in Big Data, there are gaps in knowledge about its potential opportunities and the unique computational and statistical challenges. To thrive on the opportunities that it presents, it is important that scholars explore Big Data from a critical perspective –that is, what is Big Data? Why use Big Data? How to employ Big Data? Drawing on a systematic literature review, this chapter presents an overview of Descriptive analytic methods for Big Data. The aims of this chapter are twofold: first, to draw on prior scholarly publications to explore what is Big Data and how Big Data is analysed; second, to assess the role of descriptive analytic methods in Big Data analysis. The chapter concludes with implications for both researchers and practitioners and directions for future research using descriptive analytics.

Suggested Citation

  • Nilupulee Liyanagamage & Mario Fernando, 2023. "Descriptive analytics methods in big data: a systematic literature review," Chapters, in: Shahriar Akter & Samuel Fosso Wamba (ed.), Handbook of Big Data Research Methods, chapter 18, pages 295-308, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:20820_18
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