Data and Information Inventory and Attributes - Provenance and Audit attributes for the Data and Information Inventory
Data and Information Inventory and Attributes
Chapter 26. Provenance and Audit attributes for the Data and Information Inventory
Executive Summary: Chapter Overview
IF4ITThe Bottom Line
Core Concepts
| Concept | Definition & Strategic Role |
|---|---|
| Provenance | Provenance records the origin of a data type definition or attribute value. It helps distinguish human-authored, imported, derived, calculated, and AI-generated inventory content. |
| Validation Evidence | Validation evidence identifies how a record or attribute was confirmed. It supports auditability and helps users decide whether the inventory entry can be trusted. |
| Change History | Change history captures when, why, and by whom inventory records were modified. It preserves accountability and helps reconstruct governance decisions over time. |
Quick Q&A
Question: How do provenance attributes help manage AI-generated inventory content?
Read More Below
Provenance and Audit attributes capture metadata about the inventory record itself — how it was created, when it was last updated, and the reliability of its content.
| Attribute Name | Maturity | Description and Notes |
| Record Created Date | Walk | Description — The date on which this Data and Information type record was first created in the inventory. Benefit(s) — Supports audit and compliance reporting. Source — Manual. Examples — 2024-03-15, 2023-11-01 |
| Record Created By | Walk | Description — The name or role of the individual or agent who created this record. Benefit(s) — Provides accountability for record creation and enables follow-up when record quality is questioned. Source — Manual. Examples — Jane Smith (Data Governance Lead), AI Agent (Claude, 2026-05-16) |
| Last Updated Date | Walk | Description — The date on which any attribute of this record was last modified. Benefit(s) — Enables identification of stale records not reviewed within the expected reconciliation cadence. Source — Manual. Examples — 2026-05-16, 2025-09-30 |
| Data Source | Walk | Description — How this record was initially discovered and documented. Benefit(s) — Enables data quality assessment and provenance tracing. Source — Manual. Examples — Data Catalog export (Collibra), Manual discovery workshop (2024-Q1), AI-assisted discovery (Claude, 2026-05-16), Data lineage tool export Notes — When AI-generated, document: “AI Agent (Claude, 2026-05-16) — validated by [name].” |
| AI-Generated | Walk | Description — Indicates whether this record was initially generated by an AI agent rather than manually authored. AI-generated records require human validation before being considered authoritative. Benefit(s) — Maintains transparency about record provenance. Enables targeted validation of AI-generated records before they are treated as authoritative. Source — Manual. Examples — Yes (validated), Yes (pending validation), No |
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