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Ask the Data Governance Coach: What is a Data Glossary?

Ask the Data Governance Coach: What is a Data Glossary?

This is a question I get asked a lot.  IT people are generally happy that they understand what a data dictionary is and in my experience some business people also understand what one is (and on the rare occasion may even want to refer to one). But there is often a lack of clarity over what a data glossary is.

The increasing focus on data governance and slowly maturing levels of data governance mean that the term data glossary is being increasingly heard.  But there is a great deal of confusion as the terms data dictionary and data glossary are often used interchangeably.  To add to the confusion, a data glossary is often called a business glossary, but for clarity, I will use only the term data glossary from this point onward.

The term data dictionary has been in mainstream data management speak for much longer than data glossary, so let’s start by looking at that first. According to the DAMA Dictionary of Data Management, a data dictionary is:

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“A place where business and/or technical terms and definitions are stored. Typically, data dictionaries are designed to store a limited set of meta-data concentrating on the names and definitions relating to the physical data and related objects.“

Experienced Data Analysts and Project Managers understand that building a data dictionary during a project should be a key part of your requirements development efforts. Indeed my first experience with a Data Dictionary was when I was a Project Manager for data warehouse implementation, long before I had even heard of data governance!

While it doesn’t always happen, you should definitely take the time to identify and define all of the data that is being used as part of your project and a data dictionary should be created for every system that is built or implemented in your organization.  Sadly that is not always the case and even when created they are often forgotten. I have often come across instances where it was created as a project deliverable but not maintained, or even worse, lost/mislaid over time.

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Data dictionaries should include a business definition of all terms and this should mean that business stakeholders have been involved in the creation of them.  However, because the people who are most likely to refer to a data dictionary are the IT and MI Team, they are often created without business input.  This is a pity as for the reasons I stated above, developing these as part of a requirements gathering process is an excellent way to clarify the business requirements and ensure that your new system meets them.

The first difference between the data dictionary and the data glossary is that whilst the data dictionary is seen very much as an IT-owned document, data glossaries should be created and maintained by the business.

Data glossaries are the place to document business terms along with their definitions.

 



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