We’ll be finding a reference to key data points primarily defining key business metrics.
Reference data assets and data models – Reference data is data used to categorize other data, so it’s crucial to have reference data tied to business terms to provide context on its meaning.
Data governance policies – It is indispensable to have sufficient governance around a business glossary. This will ensure that assets in the business glossary meet organizational, industry, and regulatory standards.
Classifications – Categories for data (such as restricted or sensitive data for personally identifiable information) that help organize terms and structure the business glossary.
Data lineage – Maps that delineate what data is available, where it resides, how it flows, and who uses it.
Business glossaries are a fundamental component of data governance programs and offer a range of benefits:
Improved understanding
Acronyms
Key performance indicators (KPIs)
Objectives and key results (OKRs)
Accountability
In building out a business glossary, organizations need to find the right subject matter experts to accurately define each business term. In doing so, questions of ownership can also be answered concurrently, ensuring the right individuals are accountable for their specific domains.
Policy administration
For any large organization, it is vital to be able to set data policies at a logical level, and have those policies applied consistently across disparate physical data stores. A business glossary serves a key role within that abstraction. It allows specific business terms to be ascribed different levels of sensitivity – for example, classifying all ‘customer’ data as confidential – and ensures those properties can be applied consistently to all physical representations of those assets.
Steps for building a business glossary
Now that you understand the basics of a business glossary, here are the steps for actually building this glossary:
1. Identify critical data elements
A business glossary that goes across the enterprise can house thousands of elements and terms, but there is no need to boil the ocean when you are first building a business glossary. The first step of building a business glossary is identifying critical data elements. Consider using industry standards such as ISO 27001 and 11179 to identify and prioritize these elements.
2. Identify the owners and link those to the policies and criteria
Once you have identified these elements, you need to assign ownership to them. Who creates these elements? Who approves them? Who uses them and why?
3. Build out standard operating procedures
Next, you must create policies and standards around the elements. Here you should build and document processes to assure the quality and integrity of your data. At this point, you’ll see why ownership, roles and responsibilities are critical in establishing controls. Having the right experts in the room who can define appropriate thresholds allows you to avoid a “one-size-fits-all” approach that often dooms governance programs.
4. Drive adoption among the line of business (LOB)
The fourth step is driving adoption among the business users. The business glossary is only effective if people actually use it. In order to drive adoption, you must inform business users about the business glossary’s availability, educate them on how to find it and maximize its availability, and train them to follow the standards you put in place.
The purpose of a business glossary for your organization
A business glossary’s purpose is to define terminology and provide an authoritative source for the organization. All in all, organizations use business glossaries to
Create a shared language – Define and standardize roles, responsibilities and terms to facilitate a common understanding within and across teams
Promote visibility and transparency – make it easy for everyone to discover how data is used, how it’s transformed, and how to access it
Ensure consistency – Get everyone on the same page to facilitate collaboration
A business glossary helps organizations create a business ontology, allowing employees to understand various business terms and how they relate to each other. Organizations should build a business glossary to create a shared language around data and, therefore, enable employees to communicate, collaborate, and make meaningful data-driven decisions.