Publication Date
January 2013
Abstract
This paper describes an approach to connect decision analysis models with outputs of analytic methods applied to various types of big data. Decision analysis models focus on issues of concern to a decision maker and incorporate use of a range of methods and axioms to develop insights about what the decision maker should do. In particular, decision analysis models typically use subjective judgments from the decision maker to describe beliefs about the likelihood of events and the desirability of outcomes. In order for human judgments to be improved by the availability of large amounts of data and processing power, it is necessary to define the right variables to interpolate between the data source and the decision model. Several applications are reviewed and suggest a more general approach.
Recommended Citation
Keisler, Jeffrey, "Connecting big data with big decisions: Ideas for synthesizing analytics and decision analysis" (2013). Management Science and Information Systems Faculty Publication Series. 41.
https://scholarworks.umb.edu/msis_faculty_pubs/41
Included in
Applied Statistics Commons, Management Information Systems Commons, Management Sciences and Quantitative Methods Commons