Enabling self-service BI: A methodology and a case study for a model management warehouse

David Schuff, Karen Corral (), Robert D. St. Louis and Greg Schymik
Additional contact information
David Schuff: Temple University
Karen Corral: Boise State University
Robert D. St. Louis: Arizona State University
Greg Schymik: Grand Valley State University

Information Systems Frontiers, 2018, vol. 20, issue 2, No 7, 275-288

Abstract: Abstract The promise of Self-Service Business Intelligence (BI) is its ability to give business users access to selection, analysis, and reporting tools without requiring intervention from IT. This is essential if BI is to maximize its contribution by radically transforming how people make decisions. However, while some progress has been made through tools such as SAS Enterprise Miner, IBM SPSS Modeler, and RapidMiner, analytical modeling remains firmly in the domain of IT departments and data scientists. The development of tools that mitigate the need for modeling expertise remains the “missing link” in self-service BI, but prior attempts at developing modeling languages for non-technical audiences have not been widely implemented. By introducing a structured methodology for model formulation specifically designed for practitioners, this paper fills the unmet need to bring model-building to a mainstream business audience. The paper also shows how to build a dimensional Model Management Warehouse that supports the proposed methodology, and demonstrates the viability of this approach by applying it to a problem faced by the Division of Fiscal and Actuarial Services of the US Department of Labor. The paper concludes by outlining several areas for future research.

Keywords: Business intelligence; Model management; Analytics; Modeling; Self-service (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10796-016-9722-2

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