A study of big data evolution and research challenges. (June 2019)

• Record Type: Journal Article
• Authors: Gupta, Deepak; Rani, Rinkle
• Is Part Of: Journal of information science. Volume 45:Number 3(2019)
• Page Start: 322
• Page End: 340
• Publication Date: 2019-06
• Subjects: Bibliometric study -- big data -- data analytics -- research challenges -- stream processing; Information science -- Periodicals; Information science; Periodicals; 020.5
• DOI: 10.1177/0165551518789880
• Languages: English
• ISSNs: 0165-5515

Abstract

The world is already into the information age. The huge growth of digital data has overwhelmed the traditional systems and approaches. Big data is touching almost all aspects of our life and the data-driven discovery approach is an emerging paradigm for computing. The ever-growing data provides a tidal wave of opportunities and challenges in terms of data capture, storage, manipulation, management, analysis, knowledge extraction, security, privacy and visualisation. Though the promise of big data seems to be genuine, still a wide gap exists between its potential and realisation. In last few years, there is a huge surge in research efforts in academia as well as industry to have a better understanding of big data. This article discusses the following: (1) big data evolution including a bibliometric study of academic and industry publications pertaining to big data during the period 2000–2017, (2) popular open-source big data stream processing frameworks and (3) prevalent research challenges which must be addressed to realise the true potential of big data.