Description
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.
Recommended Citation
Schymik, Greg; Corral, Karen; Schuff, David; and St. Louis, Robert D., "Designing a Prototype for Analytical Model Selection and Execution to Support Self-Service BI" (2017). AMCIS 2017 Proceedings. 14.
https://aisel.aisnet.org/amcis2017/DataScience/Presentations/14
Designing a Prototype for Analytical Model Selection and Execution to Support Self-Service BI
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.