Implementing a Business Glossary in Data Governance

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Click to learn more about author Sharad Varshney.

A business glossary is a list of data-related terms and definitions, displayed clearly and logically so everyone in an organization can access them. A business glossary is an essential Data Literacy tool and crucial for effective Data Governance. Standardization is one of the major components of Data Literacy and, subsequently, is the key driver of developing a business glossary in any organization.

In this article, we will:

  • Discuss the importance of a business glossary
  • Explain two implementation methods

Why Is a Business Glossary Important?

Without a business glossary, companies become overwhelmed with the sheer number of conflicting terms and definitions used. When there is no standardization, organizations will encounter hurdles with every key business process.

For example, from a finance perspective, if a company wanted to complete a financial reporting exercise to calculate their annual gross revenue, there would need to be a definition of “gross revenue” in place. However, your CRM system may show different numbers, their definition of revenue may be different. In your financial system, revenue is the amount invoiced, while revenue is the amount booked in a CRM system. So, when it comes to compiling the data, there will be discrepancies.

In the financial and banking sector, KPIs and terms every company reports are well-regulated, and their definitions are well-known to everyone. Accountants and banking professionals are trained to use and understand them. But when these terms are used at a project level or department level, their definitions differ quite a bit.

In other sectors, definitions are not regulated at all. Every company and department use their unique definition with assumptions.

For example, there is no standard definition to calculate the “length of stay” in hospitals in the health care sector. Every hospital reports this term in its annual balance sheet. When every hospital collects data differently and calculates the term differently, how can they aggregate?

Inconsistent definitions make it very difficult for mergers to take place. One hospital might define the length of stay as the moment a patient enters the hospital to when they leave, while another hospital might describe it as the time spent in a particular ward or from the first meeting with a doctor.

How Are Terms and Definitions Standardized?

The first step is to ask if multiple terms are in use. The ideal scenario is one where standard terms already exist, but this is usually not the case. This scenario calls for a bottom-up approach.

The Bottom-Up Approach

Businesses using this model need to create a Data Governance committee. The function of the committee is to standardize the terms used in an organization.

This is a massive challenge because hundreds or even thousands of reports are already using these terms. 

The steps for the bottom-up approach are:

  1. Catalog data
  2. Discuss and finalize terms
  3. Identify key stakeholders
  4. Analyze and consolidate terms
  5. Catalog data

The governance committee must determine where the terms are being used, how the terms are being used, and who is using them.

The Data Governance committee must then adopt a data catalog. The catalog crawls all the reports in an organization, finds the terms, and catalogs them. Through analysis, you can identify and consolidate the most critical terms in your organization.

Using a data catalog, you can quickly identify the key data owners and stakeholders. Once you get this information, you need to coordinate with the users of these terms to determine a standard definition through consensus. Finally, you need to make everyone in your company aware of the new standard terms and definitions and input them into your business glossary.

Moving forward, whenever a new data element is added, it should be signed off by the governance committee, who will create a standard definition.

Without a data catalog, it would be almost impossible to go into an organization and figure out exactly where the problems exist. There are many places to look and people to ask to find out where those applications are. And it’s too complicated to determine how we are using the terms.

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