# Data Governance

> Establish data governance — ownership, policies, decision rights, and accountability — so data is trusted, compliant, and usable across the organization. Use when designing governance operating models, assigning data owners, or fixing chronic trust and access problems.

- Skill: `itsual/data-governance` (Agent Skill)
- Install (CLI): `npx skillmds@latest add itsual/data-governance`
- Raw SKILL.md: https://api.skillmd.com/api/skills/itsual/data-governance/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: itsual (https://skillmd.com/u/itsual)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/itsual/data-governance

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# Data Governance

## Overview

Data governance is the system of decision rights and accountabilities for data assets. It answers who decides standards, who owns quality, and how conflicts are resolved.

## When to Use

- Standing up or maturing a governance program
- Assigning data domain owners and stewards
- Resolving conflicting metrics or access rules
- Aligning data use with privacy and regulatory obligations

## Core Practices

- Define governance scope by data domains (customer, product, finance, etc.)
- Assign owners (accountability) and stewards (day-to-day care)
- Set policies for quality, access, retention, and acceptable use
- Create decision forums for standards and exceptions
- Tie governance to real pain (conflicting numbers, audit findings, blocked projects)
- Measure adoption: owned domains, certified datasets, issue closure rates

## Principles

- Governance without business ownership becomes bureaucracy
- Start with critical domains, not a universal catalog fantasy
- Policies must be enforceable in tools and processes
- Trust is the product; paperwork is only a means

## Verification

- [ ] Critical domains have named owners
- [ ] Decision rights for standards are clear
- [ ] Policies connect to operational controls