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Automated Business Glossary with Qlik's AI Agent

Qlik
07/22/2026
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But, creating one retroactively is tedious, time-consuming, and usually pushed aside. The result? Teams spend hours debating definitions, questioning datasets, and making decisions based on inconsistent metrics. With Qlik Answers and the Agentic Experience, you can change that completely. Qlik's glossary agents use AI, metadata, and trusted context from your data products and apps to automatically identify, organize, and standardize business terms. Then, using natural language, you can quickly build a centralized glossary that delivers consistent, trusted definitions across your entire organization. Ready to see more? Watch the on-demand webinar for demonstrations of each agentic data engineering agent.

TL;DR

  • Business glossaries are widely recognized as valuable but rarely built because the manual creation process is too slow and resource-intensive for most organizations.
  • Qlik's Glossary Agent uses AI and metadata from existing data products to automatically identify, organize, and standardize business terms without manual curation.
  • Natural language interaction allows users to quickly build and maintain a centralized glossary that delivers consistent definitions across the entire organization.

Summary

This short product introduction from Qlik presents the Glossary Agent, an AI-powered capability within the Qlik Answers and Agentic Experience platform designed to eliminate one of the most persistent pain points in enterprise data management: the business glossary. The video opens by acknowledging that while a centralized business glossary is widely recognized as essential for data alignment, building one retroactively is so tedious and time-consuming that it is routinely deprioritized. The consequence is costly — teams waste hours debating metric definitions, questioning dataset reliability, and ultimately making decisions grounded in inconsistent terminology. Qlik's Glossary Agent addresses this directly by leveraging AI, metadata, and trusted context drawn from existing data products and applications to automatically identify, organize, and standardize business terms. Rather than requiring manual curation, users can interact with the agent using natural language to rapidly construct a centralized glossary that enforces consistent, trusted definitions across the entire organization. The video closes with a call to action directing viewers to an on-demand webinar for deeper demonstrations of the broader suite of agentic data engineering capabilities.

Chapters

0:00 - The Business Glossary Problem
0:23 - Introducing the Glossary Agent
0:39 - Natural Language Glossary Building
0:49 - On-Demand Webinar CTA

Key Quotes

0:07 "Creating one retroactively is tedious, time-consuming, and usually pushed aside."
0:14 "Teams spend hours debating definitions, questioning datasets, and making decisions based on inconsistent metrics."
0:28 "Qlik's glossary agents use AI, metadata, and trusted context from your data products and apps to automatically identify, organize, and standardize business terms."

FAQ

What problem does Qlik's Glossary Agent solve?

It solves the challenge of building and maintaining a business glossary retroactively. Without one, teams debate definitions and make decisions based on inconsistent metrics. The agent automates the identification, organization, and standardization of business terms using AI and existing metadata.

How do users interact with the Glossary Agent?

Users interact with the Glossary Agent using natural language, allowing them to quickly build a centralized glossary without requiring technical expertise or manual data entry.


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