The Importance of a Data Glossary

There are many terms and technical jargon that is associated with a business’ data structure and policies that not everyone is familiar with. In some cases, different people within the same organization have different terminologies that they use for the same item or process, leading not only to confusion but, worse, roadblocks that impede critical business processes across the board.

In order to address these issues, it is crucial for a business to have a data literacy tool that will enable those in the organization to understand the terminologies, enable collaboration in dealing with data assets, and undertake more effective data analysis work. This is where a data glossary comes in handy.

Differentiating data glossary with data dictionary and data catalog

Given the terms, many users tend to conflate a data glossary with a data dictionary. But while the two are similar in some aspects, they pertain to different resources. The data glossary defines terms so users can easily identify and collaborate using them, while a data dictionary sets and enforces various data standards, documenting origins, formats, and relationships to ensure the smooth operation of the databases.

Some also tend to confuse a data glossary with a data catalog. As with the previous case, although there are some similarities, there are significant differences, the key difference being that a data catalog acts more as a support to the creation of a data glossary.

Elements of the data glossary

A true data glossary should have the following key elements:

• Terms and definitions – provide a more consistent and improved understanding of data assets quickly and easily
• Data classification - identifies data according to specified characteristics as well as determines the relationships among data
• Reference data - categorizes data at a micro-level
• Technical metadata - so experienced data analysts can analyze data assets in the context

Benefits of a data glossary

There are several crucial business benefits of a data glossary in your organization, among them are:

• Facilitates understanding - Users can quickly and easily find definitions for terms used in their data documentation, which in turn facilitates a better understanding of the data overall.
• Improves communication – A data glossary makes communication easy with other departments and avoids confusion over data terms, ensuring more effective communication toward data-driven innovation.
• Reduces complexity and confusion - A data glossary standardizes the terms to be used in relation to data, thus resolving the conflicts that would have derailed any progress made on data-related tasks.
• Increases productivity and trust – With a data glossary accessible at any time to resolve conflicting terms, users are able to devote more time to the actual data work and make more productive business decisions.
• Establishes ownership – Data governance is a collaborative effort among all users within the organization. As such, a data glossary provides documentation of these data owners quickly and easily, as well as makes changes if necessary, thus establishing the responsibility of each user in relation to the data assets and ensuring their quality.

Building a data glossary

While each business will have different situations and needs when it comes to their data structure, the preparation of a data glossary involves the following process:

1. It is important to first determine if multiple terms are in use for certain processes and items in the organization’s data structure or if there is a standard already in place for these terms. Usually, and unfortunately, the former is often the case so a bottom-up approach is required.
2. If the organization has not set this up yet, a data governance group is to be established to standardize the terms used in an organization.
3. The data governance group determines where and how the terms are being used and who is using them.
4. The most critical terms are identified and consolidated through analysis.
5. Coordination with the users of these terms is needed to determine a standard definition through consensus.
6. An information drive is undertaken to ensure that everyone in the organization is aware of the new standard terms and definitions which are entered into the data glossary.
7. Whenever a new data element is added, it should be signed off by the governance group which will create a standard definition.

Building a data glossary is not just about formulating definitions that will be easily understood and learned by the user but also about building consensus, making sound decisions, and resolving difficult complications associated with data terms. It goes without saying that the role of the data governance group cannot be overstated enough as it will be crucial in resolving conflicts and biases associated with data and creating a coherent and comprehensive data glossary that will help ensure the business's future.