# Data Validation

> Skills for validating data integrity, schema compliance, and lineage in data pipelines.

- Skill: `gitwalter/data-validation` (Agent Skill)
- Install (CLI): `npx skillmds@latest add gitwalter/data-validation`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gitwalter/data-validation/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: gitwalter (https://skillmd.com/u/gitwalter)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/gitwalter/data-validation

---


# Data Validation Skill

## When to Use
Use this skill when you need to verify the integrity, type compliance, and business logic of data at any stage of the SDLC, particularly within ETL/ELT pipelines.

## Prerequisites
- Defined schema (JSON Schema, SQL DDL, or Pydantic models).
- Access to the target data source or artifacts.
- Validated `data-patterns.json` Knowledge Item.

## Process
1. **Identify Schema**: Select the target schema or definition to validate against.
2. **Execute Validation**: Use the `validate_schema` tool to run the check.
3. **Report Failures**: Generate a summary of violations and their impact.
4. **Remediate**: Fix the data or update the schema if it's outdated.

## Best Practices
- **Early Validation**: Run validation as close to the source as possible.
- **Automate**: Integrate validation checks into CI/CD pipelines.
- **Version Schemas**: Always use versioned schemas to avoid regression.