Physical
The actual database columns, tables, and schemas — extracted from DDL scripts, schema exports, and technical specifications.
Physical elements are where your data actually lives. Match them to business terms and you have a verified glossary.
Physical Elements
4 of 4 Inventories
189
records
127
Approved
48
Pending
14
Manual
Live counts from the agent pipeline
How records get here.
Records land in the inventory two ways — extracted from documents by an agent, or entered by your team. Both paths feed the same approval queue.
Physical Inventory Agent
AI-powered extraction.
The agent parses schemas, DDL scripts, and data dictionaries to extract column definitions with full metadata, data types, and constraints.
Processes these document types
Reads DDL, Excel schemas, and technical docs interchangeably.
Human in the loop
Manual entry and review.
Database administrators and data engineers can add columns directly or validate and approve agent-extracted schemas.
Human actions
- Add records manually
- Edit existing data
- Approve pending items
- Remove duplicates
Every AI suggestion requires human approval.
Trust scores, by source.
Every record carries a trust score based on the maturity of the document it came from. Approved technical specifications produce high-trust records. Informal notes produce low-trust ones.
High Trust
From approved specs and signed-off requirements.
Medium Trust
From draft documents and work-in-progress specs.
Low Trust
From informal docs, emails, and early drafts.
Pilot distribution
From pending to production.
Records start as pending. They must be marked use before downstream tools like lineage can pick them up.
Pending
Awaiting review
Use
Ready for lineage
Lineage
Connected to pipelines
The Physical Elements table.
Catalogue database columns with full technical metadata — schema, type, constraints, lineage candidates.
| # | Trust | Action | Column Name | Table Name | Schema | Data Type | System | Source Documentation |
|---|---|---|---|---|---|---|---|---|
| 1 | High | Use | CUST_ID | CUSTOMERS | CRM | VARCHAR(50) | CRM System | CRM Database Schema v4.xlsx |
| 2 | High | Use | ACCT_BAL | ACCOUNTS | FINANCE | DECIMAL(18,2) | ERP Platform | ERP Data Dictionary.xlsx |
| 3 | Medium | Use | TXN_DATE | TRANSACTIONS | PAYMENTS | DATETIME | Payment Gateway | Payment Schema Documentation.pdf |
| 4 | Medium | Pending | PROD_NM | PRODUCTS | CATALOG | VARCHAR(200) | Product Catalog | Product Database DDL.sql |
| 5 | Low | Pending | RISK_SCORE | CREDIT_ASSESSMENTS | RISK | INTEGER | Risk Engine | Risk Model Technical Spec.docx |
| 6 | Low | Pending | ADDRESS_LINE_1 | CUSTOMER_ADDRESSES | CRM | VARCHAR(255) | CRM System | Manual entry via UI |
This is a preview — the real interface supports full CRUD operations
Three more inventories.
Physical is one of four. Together they form your end-to-end landscape — from the source system down to the column in the database.
Tools that depend on this inventory.
Physical elements are the other half of every glossary match. Approved matches feed the Business Glossary, then roll up into the Global Glossary.
Ready to catalogue your database schemas?
We'll point IDA at your DDL scripts and data dictionaries in a 30-minute call and show you the column catalog that comes out.
Book a demo