Both business glossaries and data dictionaries sound like something you’d find sitting on the reference shelf of a library. The terms are basically interchangeable, right? Wrong! While they share some similarities, both the purpose and the content of these two documents differ substantially, and understanding those differences is the key to ensuring that business owners are using these crucial resources in the way that best benefits their operations.
What’s the difference between a dictionary and a glossary?
Before getting into the details of a business glossary and a data dictionary, having an understanding of the base words in each is key to understanding their overall differences.
A dictionary defines words. The primary goal of a dictionary is to learn the definition of an unfamiliar term. Dictionary entries are typically isolated descriptions of the individual word designed to offer familiarity and understanding of that specific term.
A glossary, on the other hand, is more contextualized. Traditionally, glossaries have appeared at the end of non-fiction books as a way to familiarize readers with individual terms in use for the specific context of that book. Glossary entries tend to be much more interconnected than dictionary entries because they include explanations of the terms’ relationships to one another.
What is a data dictionary?
A data dictionary is a technical document that defines terms specifically related to data collection, storage, and implementation. Data dictionaries are typically used by IT teams as they build, change, and maintain data systems. Most of the time, data dictionaries are not written for a general audience outside of these specific uses as they lack the contextualization that would make them accessible to people who do not have a working background knowledge of the concepts.
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What is a business glossary?
A business glossary is a much more accessible and dynamic document. Business glossaries are written with the specific context of an individual business in mind, and they are designed to ensure there is clarity, agreement, and consistency across departments. Business glossaries do define terminology as it is used within the specific business, but they also provide contextual information such as how those terms are interrelated with processes and procedures.
In short, a business glossary acts as a kind of unifying document that ensures individuals with different perspectives and areas of expertise are able to work together with the same foundational understanding of how and why they do what they do.
Why does the difference matter?
Often, businesses can make the mistake of thinking that having a data dictionary is a sufficient way to cover the definitional information needed to run the business. This mistake can result in confusion, miscommunication, and an imbalance of power.
Business glossaries help address these issues by ensuring that there is an accessible document written specifically for that individual business. This document is dynamic and organic. It grows and changes as the business does, with frequently updated entries that capture institutional changes. Over time, it becomes a kind of living history of the business, allowing new employees to get up to speed with ease and ensuring that institutional knowledge is not lost as previous employees cycle out of the business.
Business glossaries often take more time and energy to build and maintain than a data dictionary, but that’s because it is a reflection of many different people working together to ensure that they are operating from the same basic understanding. Without this kind of collaborative process, the business glossary will not be an accurate representation of how people all over the business are using terminology and making connections between processes.
Understanding the purpose of a data dictionary and a business glossary allows businesses to make intentional choices about how they build and use each document for optimal benefits.
As Director of Enterprise Analytics, James helped Thomson Reuters establish data management capabilities and an enterprise-wide analytics competency.
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