Abstract
The decision-making process is marked by two kinds of elements: organizational and technical. The organizational elements are those related to companies’ day-to-day functioning, where decisions must be made and aligned with the companies’ strategy. The technical elements include the toolset used to aid the decision making process such as information systems, data repositories, formal modeling, and analysis of decisions. This work highlights a subset of the elements combined to define an integrated model of decision making using big data, business intelligence, decision support systems, and organizational learning all working together to provide the decision maker with a reliable visualization of the decision-related opportunities. The main objective of this work is to perform a theoretical analysis and discussion about these elements, thus providing an understanding of why and how they work together.
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Poleto, T., de Carvalho, V.D.H., Costa, A.P.C.S. (2015). The Roles of Big Data in the Decision-Support Process: An Empirical Investigation. In: Delibašić, B., et al. Decision Support Systems V – Big Data Analytics for Decision Making. ICDSST 2015. Lecture Notes in Business Information Processing, vol 216. Springer, Cham. https://doi.org/10.1007/978-3-319-18533-0_2
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DOI: https://doi.org/10.1007/978-3-319-18533-0_2
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