Organisations are increasingly leveraging self-service analytics to empower business users to independently access, analyse, and interpret data for informed decision-making. Amid the surge in self-service adoption, whether business users trust the data for self-service analytics is a key concern for organisations. Drawing on information processing theory (IPT), we propose a framework that links building trust in data through data governance with uncertainty and ambiguity in a self-service environment and decision-making performance. The details of the framework explain how organisations may address uncertainty and ambiguity in the self-service environment by identifying the self-service needs, building data governance mechanisms to meet those needs, and using self-service analytics to make informed business decisions. Our study contributes to business analytics literature by examining how data governance plays a pivotal role in building trust in data to enable self-service analytics.
Patabandige, Gayani; Black, Stuart; Naseer, Humza; Cooper, Vanessa; Dias, Malshika; and Yapa, Saman, "Building Trust in Data through Data Governance to Enable Self-Service Analytics" (2023). ACIS 2023 Proceedings. 91.