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How to Use a Glossary to Model and Analyze BI Requirements

Rachael Wilterdink Rachael Wilterdink  |  
Jun 13, 2019
 
If you’re involved in eliciting, modeling, analyzing, or consuming requirements for BI projects, this post is for you. Over the next several months, we will be releasing 10 Techniques for Business Analysts (BAs) to model and analyze Business Intelligence (BI) requirements on our blog. The fourth technique in my blog series is Data Modeling.
 
The sixth technique in my blog series is Glossary. This technique harkens back to the second technique in this blog series – Data Dictionaries. Glossaries are similar, but also different.
 

What is a Glossary?

According to the International Institute of Business Analysis (IIBA®), “A glossary defines key terms relevant to a business domain.” - BABOK® v3.0
 
A Glossary:
 
  • Is a list of terms with to provide a common understanding between stakeholders
  • Provides a common language to communicate
  • Is continuously updated and accessible to all
 

What are the Elements of a Glossary?

Terms are included in a glossary when:
 
  • They are unique to a domain
  • There are multiple existing definitions
  • The implied definition is outside the team’s use
  • There’s a reasonable chance of misunderstanding
 

What Should You Consider When Creating a Glossary?

  • Definitions should be:
    • Clear
    • Concise
    • Brief
  • Acronyms should be spelled out
  • It should be easily and reliably accessible to stakeholders
  • Limit editing access to a small number of stakeholders
 
How to Use a Glossary to Model and Analyze BI Requirements
 

Pros

Glossaries are extremely useful when there are many acronyms, terms that are not generally well-known or understood, industry jargon, words that have multiple meanings, or multiple terms are used to describe the same thing.
 
I am a huge fan of Glossaries as a technique for business analysis. As a consultant, I’m often asked to go to new companies working in industries I’ve never been exposed to before. It’s like starting a new job every time I start a new assignment, and I’m expected to get up to speed fast. A Glossary helps me ramp up my knowledge quickly by defining all terms I’m unfamiliar with and getting their definitions.
 
Glossaries are easy to use, and are not extremely detailed, as compared to Data Dictionaries. Glossaries can help new hires get ramped up quickly. They can also be a source to develop a shared understanding and consistent vocabulary within an organization.
 

Cons

I typically start out my assignments by using an existing Glossary, or creating one of my own. If the organization doesn’t already have a Glossary, it can be time-consuming to find all the words and terms you’ll need to know, and get their definitions. It’s also easy to miss terms that are not as commonly used.
 
Another caution with Glossaries is that they must be maintained in order to retain value. My habit is to create a Glossary when I start an assignment, and I update it throughout my engagement as needed. That way, if I need to transfer my knowledge to others when I exit, I can save the next person the trouble of having to do the same thing.
 
As I mentioned in the Data Dictionary blog, there can be some confusion between this artifact and a Data Dictionary. The main thing to remember is that this is a more broadly available reference for an entire organization, with the business users being the primary audience. Data Dictionaries are more detailed and are meant for a technical audience. Also, if there are any items from the Glossary that are included in the Data Dictionary, they should match and not conflict in their description or definition.
 

Conclusion

Glossaries are excellent tools for helping organizations share the same vocabulary, and for people new to an organization who need to learn the local lingo. However, in order to be useful, they need to be maintained. Also, any terms included in a Glossary should match what’s included in a Data Dictionary (if there is one).
 
Next up in my blog series: Report Tables.
 

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References:
“IIBA Home.” IIBA | International Institute of Business Analysis, www.iiba.org/.
“PMI.” PMI | Project Management Institute, www.pmi.org/.
 
Business AnalysisBusiness Intelligence

 

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