Business Analytics in the Context of Big Data: A Roadmap for Research

TLDR

Academic and industry discussions at 2012–2013 ICIS events highlighted big data’s potential for decision making, identified research gaps, and noted that many developments are occurring in the practitioner community. The study proposes a big data analytics framework to bridge the gap between academic and practitioner research. The authors use practitioner interviews and literature reviews to map the current state of big data research and identify future research directions. They identify the current state of big data research and propose future research areas to improve academic relevance to practice.

Abstract

This paper builds on academic and industry discussions from the 2012 and 2013 pre-ICIS events: BI Congress III and the Special Interest Group on Decision Support Systems (SIGDSS) workshop, respectively. Recognizing the potential of “big data” to offer new insights for decision making and innovation, panelists at the two events discussed how organizations can use and manage big data for competitive advantage. In addition, expert panelists helped to identify research gaps. While emerging research in the academic community identifies some of the issues in acquiring, analyzing, and using big data, many of the new developments are occurring in the practitioner community. We bridge the gap between academic and practitioner research by presenting a big data analytics framework that depicts a process view of the components needed for big data analytics in organizations. Using practitioner interviews and literature from both academia and practice, we identify the current state of big data research guided by the framework and propose potential areas for future research to increase the relevance of academic research to practice.