A business glossary is a way used to describe the meaning of your data about your company, how it operates and the other data it gathers, by means of business terms (or other business objects). Business terms are composed standardly from names and definitions of things your company gathers data about, harmonized, and agreed upon by every responsible stakeholder. The ability to encourage interdepartmental use of harmonized metrics and definitions is what makes a business glossary such a powerful and integral approach to proper data management.
Without a business glossary, any data governance initiative is most likely condemned to fail.
In their day-to-day work reporting and BI teams need to interpret data from reports and convert them into suggestions for the management to base their next business decision on. But how can you be sure the data is being interpreted accurately and that BI teams understand and use the data correctly?
Reading a report and coming across a vague or ambiguous metric is a relatable situation. Maybe an acronym to which you can imagine ten different interpretations, a term such as “Active Customer” where the definition of “active” pretty much depends on the reader’s perspective, or a word you’ve outright never seen in this context before, such as “Godfathers”.
Well, no more. Through a business glossary two very beneficial things can be done for reporting. One for report producers and one for report consumers.
First, a business glossary gives you a full overview of what data is relevant to the company and what are its metrics. Thus, when creating a new report, BI specialists can refer to the business glossary when in doubt about whether a certain metric does or does not belong in it.
Second, it provides the ever-important context. The business glossary provides information about every metric in every report. Don’t know what makes Active Customer “active”? The definition is in the Business Glossary. This way, you can trust that metrics will always mean the same thing regardless of what department they were made in.
As an extra, Business Glossary included in Accurity comes with a plugin for browsers that makes contextualization of reports and any other text even easier. With just one click, this plugin taps into the Business Glossary. It highlights all business terms defined in it that can be found in any text currently read by the user and brings up their definitions when needed.
No business term exists in a vacuum. In the world of business everything influences everything else. Documenting how business terms (and the things they represent in real life) are connected with each other is just as important for the proper understanding of a term’s context as a harmonized definition is.
Contrary to what some people might think, a business glossary is not just a static list of definitions. It goes beyond that. Since every business term represents an aspect of your company’s business operation, they can all be connected in a fashion that reflects how the things they represent are connected themselves.
This becomes important, for example, when defining reporting metrics. To understand them, it is crucial to know how they are calculated, otherwise one can never properly grasp the data alongside these metrics. In Business Glossary, terms can be connected in a way that tells users which terms represent the aspects of one’s company’s business that are used to calculate any given metric.
And it’s not just about documenting calculations. Terms can be sorted into parent-child hierarchies, grouped by umbrella terms, or set to denote synonymous or obsolete values.
When used in tandem, a business glossary can provide business users with a basic business data model, mapping out all areas of the company’s business operations that have anything to do with data. Such a model can later on have a variety of further practical uses and we will take a look at some of them.
The main purpose and benefit of a business glossary tool is the creation of a single point of truth for everything the company keeps data about. This truth will be created to be used by everybody, and so its definition must accurately reflect the semantic needs of every interested party. How do you ensure that every potential stakeholder has their say in creating a definition which must be applicable to their use of that particular metric?
Indeed, interdepartmental communication often isn’t an easy task at the best of times. Every team has its own internal customs, ways of naming and understanding things. With widely differently specialized departments, the saying: “Two who say the same don’t mean the same”, is more truthful than anywhere else. Even basic things, such as “proposal”, can mean something completely different to a salesperson compared to a Python developer.
When starting with data governance, you want “proposal” to mean exactly one thing, for everyone in the company. A key benefit of a business glossary comes into play when you would normally have a junior business analyst discover every stakeholder and then lead lengthy email conversations, assemble requirement gathering meetings, record what every stakeholder needs for a term definition to cover… you know how it goes (or, for how long it goes on).
Instead, a business glossary has harmonization features that allow stakeholders to sort out their needs with each other via, for example, a chat room. To waste no time whenever a change is made or a message from one of them is posted in the discussion, the others can be notified by the glossary itself. And the junior business analyst can be assigned on a project where they will be put to better use.
Again, nothing should be done without purpose and working with company data is no exception. Or more accurately, nothing should be done without the correct reason, in this case. When it comes to data, business users like to have it around and reap the benefits it yields. They don’t really like to delve into the details of how the warehouses and stores for this data should be built, and they leave this complicated task in the capable hands of their trusted technical users. But can business trust technical users to build the right thing without their guidance? And if not, how can they even tell?
The short answer is, they cannot. Not without their instructions, anyway. Business and technical worlds are often quite different and their respective inhabitants do not always like having to learn the lingo of the other.
But the business glossary can help mediate between them and provide a translation of instructions.
We have talked earlier about the business glossary being able to act as a basic model of your business world, and that the model has beneficial uses. Well, here’s one. By creating a faithful representation of areas of interest the company keeps data about, out of interconnected business terms that describe what data they represent, how is the data calculated, and what is its business purpose, the business glossary can be viewed as a helpful method of creating understanding between those who define business requirements, and those who build databases.
A business data lineage that connects objects of the business glossary to a data catalog can give database modellers insight into the semantic meaning of every object, in both planned and existing databases, as well as provide visual clues that show connections between data catalog objects that share the same semantic meaning.
We have come full circle back to the issue of trusting one’s data. This time it is the quality of it being put into question. Is the business able to make informed decisions based on data that was checked, not based, on quality parameters related to the business‘ worldview, but rather a deliberate choice of the technical staff? How can business users lay tracks for data quality monitoring to drive on?
Business generally knows what their data should tell them. They are the ones who must make decisions and know what information must be available to them to support their decisions in order to be successful. What they don’t know is how data quality monitoring works. Technical specialists responsible for maintaining sufficient quality of data must therefore know what constitutes “quality of data” in the eyes of the business.
The business glossary, in this case, makes up a foundation, or a substrate, from which it is easy to define rules for working with data quality. Similar to the previous use case, you can also consider the business glossary as a translation enabler between language and thought processes of business and technical specialists.
If a business glossary is described correctly and appropriately interconnected, a business user should have no problem in formulating a data quality rule using definitions contained within the glossary. And a data steward should then have no problem understanding those rules by the means of the same glossary definitions and converting a business-defined rule into data quality measuring syntax that gives business users exactly what they want to know.
The benefits do not end there, as a business glossary tool can also allow its users to keep track of which business terms are connected to which data quality rules. That way, a new layer of traceability is created, documenting association of definitions and metrics with specific data quality measurements.
These have been some of the possible uses a company can have for a business glossary tool. Examples like these demonstrate that maintaining a business glossary is scarcely the kind of unimportant, optional busywork it is sometimes made out to be. It is, in fact, a crucial step towards any real internal effectivization in the era of digitalization and dependency of businesses on data.
And while individual use cases of companies may differ, a business glossary stays universal and provides the same benefits regardless of the data governance methodology or approach you decide to take.
If you are getting the feeling that, based on the scenarios explained above, your company might need a business glossary to effectively document and describe the data your company is interested in, there is no need to look beyond this website.
Our Accurity platform Data Catalog and Business Glossary solution, which is available on-premises or as a SaaS, is built in a way to help beginners start managing their data and later scale up the range of services according to their needs, as well as support more mature companies that would like to have a single point of the truth for their data. You can get started with our Accurity Data Catalog and Business Glossary SaaS right now, absolutely free.