Engineering and Technology
| Open Access |
DOI: Big Data Analytics in Information Systems Research: Current Landscape and Future Prospects Focus: Data science, cloud platforms, real-time analytics in IS
Yeasin Arafat , Department of Information Technology Service Administration and Management, St. Francis College, 179 Livingston St, Brooklyn, NY 11201 Dhiraj Kumar Akula , Principal Data Architect, USA Yaseen Shareef Mohammed , Master of Science Technology Management, Lindsey Wilson University, 210 Lindsey Wilson St, Columbia, KY 42728 USA Gazi Mohammad Moinul Haque , Department of Information Technology, Washington University of Science and Technology (wust), Vienna, VA 22182 Mahzabin Binte Rahman , Master of Science in Business Analytics, Trine University, Detroit, Michigan, USA Asif Syed , Master of Science Technology Management, Lindsey Wilson University, 210 Lindsey Wilson St, Columbia, KY 42728 USAAbstract
The emergence of information systems (IS) research and big data analytics (BDA) represents a paradigm shift in the world of organization choice that is shifting the field to one that is dominated by big data and technologies that enable it. This paper offers an in-depth discussion of the present situation and future of the BDA in IS, especially the revolutionary opportunities of data science, cloud-based computing environments, and real-time analytics. The study will undergo a mixed-method research design as it combines the approaches of bibliometric analysis and qualitative synthesis of 1,136 peer-reviewed articles published between 2013 and 2024 on the key academic databases. Quantitative patterns suggest a steep increase in the research of IS with machine learning, predictive modelling and cloud-based analytics architecture. Sectoral analysis shows that there are extensive and intensive application of the sector across diversified domains such as healthcare, finance, manufacturing and public administration where the real-time consideration of analytics has become very crucial in providing responsiveness and agility. The thematic forecasting plays up on areas of future expansion such as explainable AI, federated learning and quantum-enhanced analytics all of which are closely associated with the continuing development of the cloud infrastructure and advanced data science procedures and methods. Even with methodological development, there remains a problem of algorithmic transparency, data cross-sector interoperability and governance. This paper presents a prospective research agenda to the IS field and future practitioners, a point to consider in the future is an interdisciplinary cooperation, an ethically responsible development, and a strategic incorporation of scalable analytics platforms. The originality of the studies in the paper is that it is conducted on an empirical basis and has a specific narrow focus of the technology enabling the next generation of data-dependent information systems.
Keywords
Big Data Analytics, Information Systems, Predictive Modeling, Research Trends, Data-Driven Decision Making
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