This paper presents a prototype of a modeling tool specifically designed for business analysts with little modeling experience. The proposed tool has an interactive user interface for a dimensional data store that contains a library of analytical models that business analysts can evaluate and use to create models they can run on their own data sets. Using a design science approach, we review the relevant literature in self-efficacy and feedforward to provide a kernel theory that informs the design criteria met by our proof of concept prototype. Specifically, we demonstrate the prototype’s user interface with a prediction problem faced by the United States Department of Labor.
This document was originally published in 23rd Americas Conference on Information Systems (AMCIS 2017): A Tradition of Innovation by the Association for Information Systems / International Conference on Information Systems. Copyright restrictions may apply.
Schymik, Greg; Schuff, David; Corral, Karen; and Louis, Robert St. (2017). "Designing a Prototype for Analytical Model Selection and Execution to Support Self-Service BI". 23rd Americas Conference on Information Systems (AMCIS 2017): A Tradition of Innovation, 1, 651-660.