Due to the growth of data volumes, volatility and variety, business analytics (BA) become an essential driver of today’s business strategies. However, BA is mainly adopted by large enterprises because it may require a complex and costly infrastructure. As many companies strive to make better use of their data and to adopt data-driven management paradigms, cloud computing has been discussed as a costeffective approach to BA implementation challenges. To date, there has been little attention on the emerging class of analytical cloud services, “Analytics as a service” (AaaS). This article aims at demarcating AaaS as a cloud offering through an explorative research approach based on multiple case studies. Based on the analysis of 28 AaaS offerings, we derive a classification scheme for AaaS business model configurations and derive five business model archetypes. We discuss cloud computing’s implications on the business analytics ecosystem where partner networks play an important role at all levels. By clarifying the definition and characteristics of AaaS business models, our study contributes to the ‘Theory for Analyzing’ that lays the groundwork for future research.
Naous, Dana; Schwarz, Johannes; and Legner, Christine, (2017). "Analytics As A Service: Cloud Computing and the Transformation of Business Analytics Business Models and Ecosystems". In Proceedings of the 25th European Conference on Information Systems (ECIS), Guimarães, Portugal, June 5-10, 2017 (pp. -). ISBN 978-989-20-7655-3 Research Papers.