Business Glossary.
Where AI-suggested matches between business terms and database columns get reviewed, approved, and signed off.
216 business terms. 67 matched. 23 pending your review.
Business Glossary
Pending review
Customer ID
lde-001Unique identifier assigned to each customer in the system
Physical Implementations
Account Balance
lde-002Current monetary balance of the account
Transaction Date
lde-003Date when the transaction was processed
How semantic matching works.
Extract
Logical and Physical Data Elements are extracted from documents into structured inventories.
Embed
A sentence-transformer model generates semantic embeddings for every term.
Match
IDA finds the top three candidate matches per LDE, each with a confidence score.
Approve
Your team reviews and approves or rejects each suggestion — every decision is logged.
How confidence is scored.
Every match comes with a confidence score and a tier. The tier tells your reviewer how much attention each suggestion needs.
Two LDEs trying to claim the same PDE? IDA flags the conflict before you commit the match — you decide which is canonical.
Perfect Match
95–100%Definition contains the exact business term. Auto-approveable with confidence.
Semantic Match
85–94%High semantic similarity between business term and column meaning.
Fuzzy Match
70–84%Partial similarity. Always needs human review.
Everything a glossary reviewer needs.
Search & filter
Find terms by name, definition, system, or match status.
Group by anything
Organise by system, table, or flat list — your call.
Bulk actions
Approve or reject hundreds of matches in one pass.
Conflict alerts
Automatic detection when two LDEs map to the same PDE.
Audit trail
Full history of who approved what, and when.
Re-process
Re-run matching as new documents land. The glossary stays current.
What feeds the glossary.
Every match has two sides. The glossary pulls them from these two inventories.
What lives downstream.
Approved matches in the Business Glossary feed both the enterprise-wide Global Glossary and the Data Lineage graph.
Ready to build your verified glossary?
We'll run IDA against your dictionaries and show you the approve-queue in a 30-minute call.
Book a demo