Data Quality Audit

---
title: Data Quality Audit
category: data
tags: [data-quality, validation, profiling, governance, audit]
difficulty: intermediate
models: [claude, gpt-4, gemini]
---

# Data Quality Audit

Systematic data quality assessment covering completeness, accuracy, consistency,
timeliness, and uniqueness across datasets.

## When to Use

- Before starting a new analytics project (trust the data first)
- After data migration or system integration
- Regular governance audits
- Debugging unexpected analytical results
- Preparing data for machine learning models

## The Technique

Data quality is measured across five dimensions. Each dimension has specific
checks that produce actionable scores and remediation plans.

## Template