Course Description & Objectives

Academic researchers and business analysts may both “work with data,” but what that actually looks like can be drastically different. This session will guide interpreters through the contrasting mental models of data in academic and business contexts. You’ll explore how data is collected, stored, analyzed, and shared in each domain—from the citation-driven world of academic research with static files and one-time analyses, to the fast-paced, value-focused world of business data dashboards, pipelines, and KPIs. By understanding these differences, interpreters will be better equipped to anticipate terminology, clarify intent, and support meaning-rich interpretations in data-heavy environments.

Upon completion of this session, participants will be able to:

• Describe at least three key differences in data management between academic and business settings.
• Accurately list two common tools or workflows used in each context.
• Create a visual or written ‘mental map’ of data concepts for one of the two domains.
• Provide three examples of terminology or jargon that differ in meaning between academic and business settings.