What is a glossary?

A glossary is a list of terms that is organized in a specific way to help users understand their data assets. For example, terms like cost, P&L, and revenue can be used to group and search all financial data assets.

Using familiar terminology helps people quickly understand the data and its context. This is a crucial element of data governance since it adds business context to the data initiatives of an organization.

In Atlan, glossary terms can be attached to any data asset and leveraged to power quick and easy data discovery.

Why do I need a glossary?

In today's diverse data teams, which include people from different backgrounds and use cases, not all of them think about their data in the same way.

For example, one team might think that a particular metric is showing an annualized rate, but the actual rate may be calculated quarterly. This could lead to some real confusion down the road. Defining data terms and sharing those definitions across your team can make a huge difference to data users at all levels of the organization.

For teams made up of data analysts, data engineers, data scientists, and decision makers, having a shared language is an important step towards ensuring better collaboration. Building a glossary allows your team to define the metrics, columns, and assets with the same meaning for everyone.

Highlights of the Atlan glossary

Here's how the Atlan glossary can help your organization:

• Powers search and makes it easier to discover data assets
• Encourages the creation, maintenance, and enrichment of business and functional terms due to their direct and visible use in searches
• Allows crowdsourcing the task of attaching appropriate glossary terms to data assets
• Supports automated metadata management through auto-glossary suggestions from the Atlan bot

Anatomy of the Atlan glossary

Atlan gives users the option to build hierarchical glossaries. A glossary term is the lowest unit that can exist independently inside a glossary. These terms can then be grouped into categories and linked together as related terms.

Let's look at how terms and categories work together to build a glossary.

Term

• A term is the lowest unit that is unique to each glossary.
• It describes the content of the data assets in a useful and precise way.
• It can exist independently, without belonging to any particular category or subcategory.

Category

• A category is a way of organizing the terms in a glossary.
• It can be used to group together similar terms.
• Subcategories can be added within categories to provide more context in a glossary.

Associated terms

With associated terms, you can define semantic relationships between your terms. These provide additional context for common definitions in your organization. 

Related term

• Similar in definition — serves the purpose of a "see also" section in a dictionary.
• Client is a related term for Customer.

Recommended term

• Preferred form of usage for the current term applied.
• User may be preferred over Customer in the context of your organization.

Synonym

• Interchangeable in meaning as another term.
• Glossary and Dictionary, or Client and Customer.

Antonym

• Opposite in meaning to a particular term.
• Minimum is an antonym for the term Maximum, or Loss and Profit are antonyms.

Translated term

• Translated version of the same term in additional languages. 
• Cliente is the Spanish term for Customer.

Valid values for

• Defines values that are considered appropriate for a related term.
• Red, Green, Blue, and Yellow are valid values for the term Color.

Classifies and Classified by

• These have a reciprocal relationship that helps provide more context for both terms.
• Country classifies United States, while United States is classified by Country.