![]() ![]() ![]() It’s one thing to understand a business glossary at a high level, but now what does a business glossary really look like and what’s in there? ContentĪ business glossary at its highest level should include the below four components and all should have relations to each other. For example, a legal entity identifier is represented as a twenty-digit alphanumeric code, while a social security number is represented as a nine-digit number. A data dictionary would not only capture those data elements but also describe how they are represented. Show the relationships between data assetsĮxpanding on the previous example of a ‘customer,’ a data dictionary would detail the specific data elements that relate to each ‘customer.’ For example, a corporate customer could be uniquely identified using a ‘legal entity identifier’ while a retail customer might be identified using a social security number (or other comparable identifier outside of the US).Provide consistency in data collection and use across tools.Ensure agreement and consistency between business content and technical dataĭata dictionaries, on the other hand, describe specific data elements in a way that databases can understand.Give visibility into how vocabulary may differ across departments.Create a shared language around data related terms.Organizations use a business glossary to: People often confuse the meanings of a business glossary and a data dictionary, but they are two distinct tools that work together to make an organization’s data more meaningful.Ī business glossary is concerned with defining business terms from a logical perspective in a way that humans can understand. What is the difference between a business glossary and a data dictionary? For example, by ascribing a level of security classification to each business term, organizations can set policies and manage access controls at a logical level and have those applied consistently across disparate physical data stores. It helps recognize relationships by identifying similarities between terms, potentially reconciling differences in interpretation, and promoting understanding of data in a business context.Ī business glossary can also be a crucial tool for managing data policies. Maintaining this business logic is crucial for the way organizations map out their data assets. When it comes to governing data, a business glossary serves as a foundational artifact it ensures that data elements can be classified logically in a business context. Why is a business glossary important?Ī business glossary is important because it helps an organization create a common business language, allowing people to better communicate and collaborate. A chief risk officer may view corporate customers as legal entities, while a marketing professional may view that same customer as a collection of individual persons. Differences could also exist internally, depending on one’s perspective. In other cases, differences could be down to the entity in question – for example, a retail bank would see customers as natural persons, while a corporate bank would broadly see them as companies. For example, a customer could also be called a buyer or purchaser, while a vendor can be referred to as a supplier or seller. ![]() In some cases, differences can be semantic. Read their customer story and get started with us now. Find out how Collibra’s data governance and catalog initiative automated Lockheed Martin’s data discovery and preparation process.
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