Data Glossary: Talking to the business


 Have you ever gone into a meeting with key business stakeholders and left more confused than you were when you went in?  When you think back about that meeting, did it seem like the two groups in the room were not speaking the same language?  You are probably not all wrong if you thought that.  You see, even if both parties were talking the same language, how they defined their words was probably different.   So, do you want the decoder ring?

By The Power Of The Data Glossary!

When you are facing this problem, you are missing a data glossary.  This is a data governance component that is very special.  Do not confuse it with the data dictionary.  A data dictionary is a metadata store about columns and the data in the columns.  More factual verbiage like: Column Color holds a list of colors available for a product. 

A data glossary is a business-managed list of terms that provides direction or helps people to understand a business process.  A great example of a data glossary entry would be INCO terms.  If you are a shipper or if you deal with shipping your product, INCO terms are second nature to you.  If you do not fall into these categories, do you know why INCO terms are important?  In the world of invoices, how do INCO Terms impact you?

If you had a well-defined data glossary, you would know that a big part of INCO terms has to do with who’s responsible for the shipment at a specific point.  For example, once the product is loaded on the truck, who is responsible for it?  If the producer is still responsible for the product when it is on the road, they will have to do a few extra things, like make sure their insurance will cover damages if anything happens.  Also, when you invoice the customer depends on when the customer takes responsibility for the shipment.  You see, this one term has major financial impacts.

Navigating Data Assets with Confidence

What other practical things can a business get out of a well-defined business glossary?:

  • Easily Find Relevant Data: By searching or browsing the glossary, users can quickly identify the specific datasets and metrics they need to address their current business objective.
  • Understand Data Context: The glossary provides crucial context, ensuring users understand what each data point represents and how it should be used.
  • Trust the Data: Clear definitions, combined with the other pillars of data governance (quality and lineage), foster trust in the data, encouraging users to leverage it for insights. 

The Essential Role of Business Buy-in and Ownership

Just by the nature of what a data glossary is, you can tell this cannot be a component that is only managed by IT.  The success of a data glossary hinges on strong business buy-in, particularly from Subject Matter Experts (SMEs) within the business units. These individuals are the most knowledgeable about how data is used in their day-to-day operations and how business terms are defined in practice. It's crucial that they:

  • Take Ownership: Business SMEs should own the definition of business terms, ensuring accuracy and relevance. 
  • Contribute Expertise: They bring invaluable context to term definitions, including nuances and specific applications within their domains.
  • Validate Definitions: Their review and approval of definitions are critical for ensuring the glossary's accuracy and usability. 

Without active involvement from the business, a data glossary risks becoming a technical exercise that lacks practical value, potentially being ignored or becoming outdated. 

The Positive Impact on Business Decisions

What can happen when IT and the business team up?  Insights happen!  When business terms are properly defined and understood across the organization, the positive impact on business decision-making is profound:

  • Clarity and Consistency: A standardized vocabulary eliminates confusion. For example, if "customer" means something different to sales, marketing, and finance, reports on "customer churn" or "customer lifetime value" will be inconsistent and unreliable, potentially leading to flawed decisions
  • Faster and More Informed Decisions: With clear definitions, decision-makers can confidently interpret data and reports, leading to faster, more confident decisions based on accurate information
  • Improved Collaboration: When everyone is speaking the same data language, collaboration across departments becomes smoother and more efficient 

The Stepping Stone to Self-Service BI

A robust data glossary is foundational for an organization moving towards self-service Business Intelligence (BI). Self-service BI empowers business users to access and analyze data independently, reducing reliance on specialized data teams. However, this only works if users can:

  • Understand the Data: A glossary provides the necessary definitions to interpret data correctly
  • Trust the Data: If users don't understand the data, they won't trust it, undermining the effectiveness of self-service tools. 
  • Collaborate Effectively: A common language facilitates smoother communication and collaboration, allowing teams to work together on data projects without misunderstanding or rework. 

Without a strong data glossary, self-service BI initiatives can quickly devolve into confusion, contradictory reports, and a lack of trust in the data, ultimately hindering the organization's ability to become truly data-driven. 

A strong data glossary is an investment in clear communication, better decision-making, and a truly data-driven culture. The data glossary is the decoder ring you are looking for. 

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