---
title: "MDLH: Audit glossary health at scale"
url: "https://atlan.com/demos/mdlh-audit-glossary-health-at-scale/"
description: "Surface every duplicate, stale term, and gap in your glossary with a single query — then fix hundreds of terms in one pass."
format: "Video"
video: "https://videos.ctfassets.net/nwa1c00rtgxb/6dscMs1JUDVNxS6TTlPugE/2158b6f88a6798125670efdc33963926/MDLH_-_Audit_glossary_health_at_scale.mp4"
content_purpose: ["Product Overview"]
target_persona: ["General", "Data Analyst", "Data Governance Lead", "Business User"]
journey_stage: ["S2 - Discovery", "S3 - Solution Design", "S4 - Business Case", "C1 - Onboarding", "C2 - First Value", "C3 - Adoption"]
use_case_context: ["Training"]
product: ["Context For AI - Business Graph"]
content_type: "video transcript"
transcript_source: "none"
---

# MDLH: Audit glossary health at scale

Summary of the video at https://atlan.com/demos/mdlh-audit-glossary-health-at-scale/. A transcript has not been published yet.

<!-- Body: no transcript published yet; summary from the Contentful entry. -->

Surface every duplicate, stale term, and gap in your glossary with a single query — then fix hundreds of terms in one pass.

Transform your glossary from an unauditable black box into a clean, queryable inventory. Pull every term, definition, owner, category, and linked asset into one result set, then use the output three ways: enrich in bulk through Atlan’s upload template, feed definitions into your AI context layer, or detect the duplicate terms that are silently causing metric discrepancies across your teams.