IDA uses sentence transformer models to find potential matches between business terms and database columns
LDEs and PDEs extracted from documents to inventories
Sentence transformers generate semantic embeddings
AI finds top 3 candidate matches per LDE with confidence scores
Humans review and approve or reject each suggestion
IDA detects different types of matches based on how the terms relate to each other. Perfect matches occur when definitions are semantically identical.
Perfect Match (95%+)
Definition contains exact business term
Semantic Match (85-94%)
High semantic similarity between terms
Fuzzy Match (70-84%)
Partial similarity, needs human review
Conflict Detection
When a Physical Data Element is matched to multiple Logical Data Elements, IDA detects the conflict and prompts you to resolve it.
Conflict Detected
Physical element CUST_ID is already mapped to Customer Identifier. Approving this will decline the conflicting mapping.
Find terms by name, definition, system, or match status
Organize terms by system, table, or flat list
Approve or reject multiple matches at once
Automatic detection of conflicting mappings
Full history of who approved what and when
Re-run matching after adding new documents
Start reviewing AI-suggested matches and build your single source of truth for business terms.