Data Quality

Use this skill when the user needs trustworthy datasets, not just successful pipeline runs.

Default stance

• Prevent bad data early when possible
• Validate transformed outputs before publishing them broadly
• Make metric definitions reviewable and owned
• Combine warehouse constraints with pipeline-level tests

Working approach