Table of Contents

Share
Subscribe to our blog

Stay in the loop on all things Metadata, LLM Governance, GenAI, and Semantic Data Fabric. By subscribing you’re agreeing to the illumex Privacy Policy.

Submit this form to subscribe to illumex Blog. Your privacy is important; we won’t share your details. Use ‘unsubscribe’ in the blog email digest to stop receiving Metadata, Data Fabric, and LLM Governance content.

Table of Contents

Share
Subscribe to our blog

Stay in the loop on all things Metadata, LLM Governance, GenAI, and Semantic Data Fabric. By subscribing you’re agreeing to the illumex Privacy Policy.

Submit this form to subscribe to illumex Blog. Your privacy is important; we won’t share your details. Use ‘unsubscribe’ in the blog email digest to stop receiving Metadata, Data Fabric, and LLM Governance content.

Who Cares about Business Terms?

This question keeps cropping up either in people’s minds or out loud and there’s a good reason for it.

Over the past decade or so, different companies have embarked on Data Governance projects, and the vast majority of those ran into creating a Business Glossary as part of those projects.

When looking at the Business Glossary portion of the Governance project, the first item they wanted to tackle was to interview Business executives in order to document Business Terms. After all, Business Terms are what matters in a Business Glossary, right?

Well, no, I don’t think that is right at all.

As a matter of fact, I think it is that exact approach that has failed so many Business Glossary initiatives and, consequently, their related Governance projects.

Spoiler – Business Terms become relevant and important when two conditions are met:

  1. When they are part of a Business Question or a Business Metric, in other words, a useful business analysis.
  2. When they are clearly and accurately connected to the data layer.


Let me elaborate…

The concept of Business Terms is fairly straightforward, and a quick Google search found this description: a business term is a word or phrase that describes a concept that is used in a particular branch of business.
That’s hard to argue with and is the general consensus amongst other sources that I found. However, in my view it misses a very important part when looking at the practical application of Business Terms – it also needs to be useful.

Critical Factor one: Usefulness

If a company sets a goal of documenting every Term that was simply “used in a particular branch of business” it would be an endless project that would quickly decline in value and would lose the interest of stakeholders. This will result in a complete lack of adoption and subsequently a failed data cataloging project (sadly this is a very common outcome).

However, when focusing on Terms that appear in popular and highly-used analyses, it changes everything. It is a fundamental change in approach and outcome because:

     a. It provides a clear prioritization rule – invest effort in the most useful Terms
     b. The effort of documenting Terms can easily be tied to business value and usefulness.

So, how do we determine the usefulness of a Business Term?

That’s actually really easy – Usefulness = the appearance of a Term in Business analyses divided by the total number of analyses.
Assuming we aggregate synonyms and acronyms (Customer, Cust, Account, Client, Clnt), we can measure the number of times “Customer” appears in analytics. When measured against the total number of analyses we run, we get a good measure of how often a Term is used relative to other Terms. Popularity is also an important measure to add – Not just the number of total Business Analyses but a factor of how often those analyses are run.

Terms such as Customer, Game, Student, Order, or Employee will appear very high on the priority list as they are likely to appear in many Business Analyses and are likely to be run frequently (i.e. they are popular).

Critical Factor Two: Connecting to data

Simply documenting and describing Terms is far from enough. Frankly, it is the easy part of the process but it is only half the job. Without the next step, all the Terms we document and describe will sit on a shelf (or Confluence or Excel) collecting dust and the time you spent and took from others will be wasted.

In order to complete the process of making a Business Glossary useful, and important and to extract enterprise-wide value from it, it must be accurately and directly connected to the data layer.

This isn’t news, every Data Catalog solution out in the market gives the option to do this. The problem is that it needs to be done manually which creates endless problems and, again, is a very common point of failure for these solutions. When a project fails at this stage, the cost in time, outsourced resources, and software licenses are extreme.

There are ways of doing this not just accurately but automatically. The reason automation is so critical is that Metadata is extremely fluid. There are constant changes, additions, and deletions. We not only need to build smart, accurate relationships, but we also need to monitor and maintain them.

There are ways to do this and, yes, the entire illumex solution is designed to tackle this very issue, but let’s get back to our question – Who cares about Business Terms?

If we have achieved the two critical factors above, the result will be that any Business executive or decision maker can ask a business question, the definition of the terms they use will be crystal clear and, equally as important, those terms will have a single “data twin”. Each term will point to the source table and column that is best used for that business question.

There are a lot more details on how to achieve this ( reach out for a demo 🙂 ) but the answers to who cares about business terms are – Well, anyone who cares about their questions being answered accurately and reliably.

In today’s business, this should practically be everyone. Everyone should care about Business Terms. When the Terms and the entire Business Glossary are created accurately and monitored regularly for maintenance, they are the foundation for fast, accurate, and impactful decision-making.

Photo by Joshua Hoehne on Unsplash

Related Posts

Generative Semantic Data Fabric - don't get RAGged by your RAG

Don’t Get RAGged by your RAG: Why Generative Semantic Fabric is the Future

So, you’ve hopped on the Retrieval Augmented Generation (RAG) bandwagon. It’s the popular choice, and...

Read More >>

Resilience and Revolution of Business Intelligence In the Age of GenAI

Embracing the Future: The Ongoing Evolution of BI Welcome to the final, 8th part of...

Read More >>
Subscribe to our newsletter

Submit this form to subscribe to illumex digest. Your privacy is important; we won’t share your details. Use ‘unsubscribe’ in the digest to stop receiving Metadata, Data Fabric, and LLM Governance content.

Stay in the loop on all things Metadata, LLM Governance, GenAI, and Semantic Data Fabric. By subscribing you’re agreeing to the illumex Privacy Policy.

We use cookies to help personalize content, tailor and measure ads, and provide a safer experience. By continuing to use this website you consent to the use of the cookies in accordance with our Cookie Policy.

Contact us

Reach out to learn more or request a demo