TY - JOUR
T1 - Business analytics in the context of big data
T2 - A roadmap for research
AU - Phillips-Wren, Gloria
AU - Iyer, Lakshmi S.
AU - Kulkarni, Uday
AU - Ariyachandra, Thilini
N1 - Publisher Copyright:
© 2015 by the Association for Information Systems.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
KW - Big data
KW - Business analytics
KW - Business intelligence
KW - Data governance
KW - Data scientist
KW - Decision support
KW - Framework
KW - Unstructured data
UR - http://www.scopus.com/inward/record.url?scp=84940369594&partnerID=8YFLogxK
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U2 - 10.17705/1cais.03723
DO - 10.17705/1cais.03723
M3 - Article
AN - SCOPUS:84940369594
SN - 1529-3181
VL - 37
SP - 448
EP - 472
JO - Communications of the Association for Information Systems
JF - Communications of the Association for Information Systems
ER -