Working with Business Glossaries in DataHub 

Outline of this demonstration (transcript below)

I. Introduction

• Purpose: Learn how to work with the business glossary in DataHub
• Value: Establishes common vocabulary across the organization
• Benefit: Ensures consistent understanding of data terms
• Goals by end of demo:
  • Create glossary terms
  • Organize terms hierarchically
  • Link terms to data assets using Web UI

II. Understanding Business Glossary

• Definition: Standard definitions for business terms used throughout organization
• Conceptual model: Think of it as a dictionary for your organization's data language
• Purpose: Provides common vocabulary and shared understanding

III. Creating a Glossary (Live Demo)

• Navigate to Glossary section in side navigation bar
• View existing glossaries
• Click "Create Glossary"
• Provide information:
  • Name (example: "Marketing Terminology")
  • Description in documentation field
• Click "Create"
• Result: Glossary serves as container for related business terms
• Note: DataHub supports multiple glossaries for different purposes

IV. Adding Business Terms

• From glossary page, click "Add Term"
• Example: Create "Customer Acquisition Cost" term
• Provide description in Documentation field
• Verify glossary association (Marketing Terminology)
• Click "Create"
• Result: First business term with clear definition for organization reference

V. Hierarchical Organization of Terms

• Capability: Terms can be organized hierarchically
• Demo: Create related term
  • Click "Add Term" again
  • Name: "CAC Payback Period"
  • Add description in Documentation field
  • Click "Create"
• Establishing relationships:
  • Access term settings
  • Go to "Related Terms"
  • Add appropriate relationships
• Result: Parent-child relationship creating logical hierarchy of concepts

VI. Linking Terms to Data Assets

Dataset-Level Linking

• Navigate to search bar
• Search for relevant dataset (example: Marketing Schema)
• Open dataset page
• In Summary tab, scroll to Terms section
• Click "Add Term"
• Select term (example: Customer Acquisition Cost)
• Save

Column-Level Linking (Granular)

• Click into specific dataset
• Navigate to individual column
• Click to add term directly to column
• Result: Users viewing dataset or column see business definition with clear context

VII. Developer/Automation Options

• REST API for creating glossaries programmatically
• Python SDK for adding terms
• Use cases:
  • Bulk importing terms from existing glossaries
  • Importing from spreadsheets
  • Automated glossary management
• Benefit: Automation for large-scale operations

VIII. Discovery and Usage

Search Functionality

• Use search bar from any page
• Search for terms (example: "acquisition cost")
• Terms appear in results

Browse Functionality

• Navigate to Glossary section
• Browse all available terms

Term Page Contents

• Term definition
• Related terms
• Linked assets
• Benefit: Easy access to standard definitions and relevant data discovery

IX. Recap & Conclusion

What Was Covered:

1. Created glossary for marketing terminology
2. Added business terms with clear definitions
3. Organized terms in hierarchy
4. Linked terms to relevant data assets (dataset and column level)
5. Explored API options for developer automation

Key Takeaways:

• Essential for: Data literacy and governance
• Ensures: Everyone speaks same language when discussing data
• Bridges: Gap between technical and business teams
• Flexibility: Intuitive Web UI or developer APIs
• Result: Comprehensive business glossary that enhances data catalog

Call to Action:

• Build and maintain business glossary in DataHub
• Use it to enhance organizational data literacy

=== TIMESTAMPED TRANSCRIPT ===

[0.00s - 10.16s]: Hello, everyone. In this video, I'll demonstrate how to work with the business glossary in
[10.16s - 15.08s]: DataHub. A business glossary is essential for establishing a common vocabulary across
[15.08s - 20.76s]: your organization, ensuring everyone understands data terms consistently. By the end of this
[20.76s - 25.64s]: short demo, you will see how to create glossary terms, organize them hierarchically, and
[25.64s - 31.68s]: link them to data assets using DataHub's Web UI. Let's start with a quick overview of
[31.68s - 36.88s]: what a business glossary is and why it matters. A business glossary in DataHub provides
[36.88s - 41.40s]: standard definitions for business terms used throughout your organization. Think about
[41.40s - 47.80s]: as a dictionary for your organization's data language. Now let's see the business glossary
[47.80s - 54.84s]: in action. First, we'll need to create a glossary to hold our terms. And DataHub, you
[54.84s - 59.60s]: can have multiple glossaries for different purposes. I'll navigate to the glossary section
[59.60s - 66.24s]: in the side navigation bar. And here we can see existing glossaries. For a new one, I can
[66.24s - 74.76s]: click Create Glossary. I can give it a name. We'll go with Marketing Terminology. And I
[74.76s - 83.48s]: can give it a description in the documentation field here. I can click Create and our glossary
[83.48s - 91.00s]: is ready. This glossary will serve as a container for related business terms. Now let's add
[91.00s - 96.60s]: a business term to our glossary. From the Marketing Terminology Glossary page, I'll
[96.60s - 109.16s]: click Add Term. Let's create a term for customer acquisition cost. I can then give it a description
[109.16s - 119.04s]: in the Documentation field. I can see that it's part of the Marketing Terminology Glossary
[119.04s - 126.16s]: group. And click Create. Great. We created our first business term with a clear definition
[126.16s - 132.48s]: that everyone in the organization can reference. Similar to domains, glossary terms can be organized
[132.48s - 138.40s]: hierarchically. Let's create a related term under customer acquisition cost. First, I'll
[138.40s - 149.40s]: create Add Term again. This will be CAC Payback Period. I can give it a description in the Documentation
[149.40s - 159.96s]: field and create it. I now have both terms. And now, if I want to have it as a related term
[159.96s - 166.96s]: to customer acquisition cost, I can click in here, go into related terms and add it appropriately.
[168.40s - 178.00s]: Now, we have a parent child relationship between our terms creating a logical hierarchy of related
[178.00s - 184.96s]: concepts. One of the most powerful features of the business glossary is the ability to link
[184.96s - 190.12s]: terms to actual data assets. Let's connect our customer acquisition cost term to a relevant
[190.12s - 201.92s]: data set. I'll navigate to the search bar and search for a data set. Here, I can find
[201.92s - 208.36s]: our Marketing Schema and open it. In the Summary tab, I'll scroll down to the term section.
[208.36s - 218.84s]: I can click Add Term. Here, I can find my customer acquisition cost term and add this. You
[218.84s - 226.96s]: can also link terms at a more granular level. If I click into any of the data sets here, I can go
[226.96s - 238.44s]: to the actual column and click in here and add the term to the column itself. Now users viewing
[238.44s - 242.84s]: this data set or column will see the business definition creating clear context for the data.
[242.84s - 250.60s]: As with domains, the data hub provides APIs and SDKs for developers who want to programmatically
[250.60s - 256.84s]: manage the business glossary. If you prefer a developer workflow, you can create glossaries via
[256.84s - 266.12s]: the rest API. And you can add terms using the Python SDK. This approach is particularly useful
[266.12s - 272.68s]: for bulk importing terms from existing glossaries or spreadsheets. Now let's see how users
[272.68s - 279.32s]: can discover and use glossary terms. For many pageant data hub, I can use the search bar. If I
[279.32s - 287.24s]: search for acquisition cost, our term appears in the results. I can also browse all terms by
[287.24s - 296.04s]: navigating to the glossary section. Clicking on a term shows its definition, related terms,
[296.04s - 301.64s]: and linked assets. This makes it easy for users to find standard definitions and discover relevant
[301.64s - 307.88s]: data assets. That wraps up our demo on the business glossary and data hub. To summarize,
[307.88s - 313.08s]: we created a glossary for marketing terminology. We added business terms with clear definitions.
[313.48s - 318.84s]: We organized terms in a hierarchy. We linked terms to relevant data assets and we explored how
[318.84s - 325.80s]: developers can use APIs for automation. I will maintain business glossary is essential for data
[325.80s - 330.76s]: literacy and governance. It ensures everyone speaks the same language when discussing data,
[330.76s - 336.04s]: bridging the gap between technical and business teams. Whether you use the intuitive web UI
[336.04s - 340.76s]: or the developer APIs, data hub makes it easy to build and maintain a comprehensive business
[340.76s - 347.72s]: glossary that enhances your data catalog. Thanks for watching.