Clara Yeung

Creating a dynamic business glossary can empower data owners at your institution to govern their data. Without a business glossary, terms can be applied differently and as a result, two reports generated by different end-users may provide different answers to the same question. For example, in terms of enrolment, does your institution consider enrolment as the admission of a student into a program, the registration of a student into a course, or a combination? Does the definition depend on which department you ask?

Language is an imperfect tool for communication – signifiers can reference more than one concept, depending on the context – think of how, “she’s running” could be an answer to “who is running in the marathon?” or to “who is running for mayor?”. For business terminology, different use cases can keep a term’s definition in flux if it is not pre-defined for the organization and made available across departments.

Ironically, the term business glossary is itself often incorrectly interchanged with the terms data glossary or data dictionary. Whereas a data glossary defines technical data terms like schemas or tables, a business glossary defines business concepts for the company or institution. The objective of a business glossary is to define common vocabulary to create consistency in a term’s usage. Consequently, implementing a business glossary helps organize data assets by providing a framework for defining a standardized set of data concepts and then associating them with the physical assets that exist within your complex data ecosystem. This is independent from any specific database, platform, or vendor.

Establishing a common vocabulary eases collaboration across business and technical communities at an institution. Business glossaries therefore allow for linking datasets and elements to business terms, empowering individuals to make informed-decisions backed by reliable data. Business glossaries are the bedrock of data governance as they allow for the development of rules, policies, and classifications of data elements. With a business glossary in place, end-users are able to quickly discover datasets as they relate to business terms, reducing unnecessary onboarding of similar data by different users.

As champions of the value of reliable data, we strongly advocate for implementing a business glossary as a means to achieve your institutional goals. If you are interested in learning more, subscribe to our newsletter, reach out to us by email, or book a session with us – we are always into talking data!