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In delivering Data Governance as-a-Service (DGaaS) for our customers, I’ve come to appreciate that a business glossary is more than just a ‘dictionary’, more than a list of words and their definitions. It is the first step into a bigger world of communicating the ‘context’ and ‘semantics’ of meaning which not only helps organisations today, but paves the way for the future of data management.

What is a business glossary?

Simply put, a business glossary is a list of terms and their definitions. By standardising terms and concepts, it ensures that all stakeholders are using the same language and terminology when discussing anything and everything related to their business operations, products and services.

From a data management perspective, it is a crucial element to get right as the same term can be used to mean different things in different contexts, which can lead to confusion and errors. A business glossary provides a standard definition for terms to ensure everyone across an organisation is on the same page; effectively, it improves communication and collaboration, and helps prevent errors that can result from ambiguity and misunderstandings.

How can it add value?

Business glossaries are fairly common within data catalogues, applying standardised definitions to drive a common understanding, however this is just the first step of the ladder of semantics to driving meaning and context. It can also incorporate relationships between terms such as synonyms, antonyms and hierarchies; all of which can help data stewards, owners and users to find the right term and use it correctly.

By facilitating effective communication and understanding of key terms, a business glossary can contribute to improved decision-making and better business outcomes.

The future of business glossaries

Drawing inspiration from Dr Harald Sack’s lectures on Semantic Web Technologies, I wanted to share two definitions.

  • Semantics: the branch of linguistics and logic concerned with meaning.
  • Ontology: a set of concepts and categories in a subject area or domain that shows their properties and the relations between them.

Presenting a continuum of Ontology “types”, Dr Harald Sack shares one model of structuring knowledge to drive understanding and meaning beyond definitions. It is focussed on the ability to derive knew knowledge if you understand the contextual model; from controlled vocabularies and glossaries to a detailed model of how things “are” with associated logical rules and constraints. While this may seem ambitious and remote, in the not-so-distant future, I can see a world where a data catalogue can show deduced information alongside a semantic model next to the data it actually has in its database.

In the meantime, the interim steps provide some interesting opportunities driven by the idea of introducing relationships between terms to create an advanced or comprehensive business glossary. Tools like Accurity already provide the ability to link terms in its glossary with different types of relationship. If you apply a bit of effort to capturing this sort of information, storing it in a glossary should be straightforward to include the following:

  • Thesauri: adding synonyms, antonyms and related terms to the glossary.
  • Taxonomies: adding a hierarchy of classes, to link terms to their superclass(es) or subclass(es).

Image: An adapted diagram inspired by Dr Harald Sack’s lectures on Semantic Web Technologies

So why would you spend the time and effort to move further along this sliding scale?

Starting from the lower end of the scale, business glossaries are focused on driving down ambiguity and misunderstandings. Then by adding synonyms, antonyms and a taxonomy, it can aid the use of the glossary by helping users find the term they might be looking for or to discover terms they didn’t know existed. Beyond that, the benefits become more apparent as we adopt and integrate systems to begin suggesting, supporting and automating processes.

To help illustrate this progression, below is a sample of how this could develop:

The Value of a Comprehensive Business Glossary

A comprehensive business glossary that goes beyond simply the definition of terms will become a valuable resource not only for data analysts and others who need to use the correct terminology in their work, it should also enable ML and AI systems to function accurately and effectively.

The semantic web focusses on making this information machine-interpretable and facilitates large language models like ChatGPT, so that programs can use the applied semantics to ‘do things’ like infer new information. In time, when private chat AI programs are introduced to organisations, the ability to ‘tune’ them using your own private semantic information will ensure that staff are interacting with a knowledgeable AI that also happens to be familiar with your organisation’s way of working. By going beyond the basics and creating an ‘advanced’ business glossary that is more intuitive to users, it should increase its usability and therefore should drive adoption.

Ultimately, the goal of a business glossary is to ensure that everyone in an organisation agrees on what things mean and a comprehensive glossary is an important step towards achieving that goal. However, the benefit of a business glossary is not its existence but having everyone agree on what things mean… essentially, a business glossary is only of use if people choose to use it.


Looking for support to operationalise this at your organisation? We stand ready to help:

Allan Watkins

At the heart of Allan's professional journey, spanning more than 26 years, lies a deep-seated passion for acquiring knowledge and understanding the mechanics behind how things operate. His thought leadership content mirrors this curiosity, enabling readers to broaden their understanding of data governance and its complex web of policies.

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