Schema validation checks whether model inputs match expected fields, types, columns, and categories. In production, it catches erroneous inputs before they distort downstream models. section 14.3.6
A practical validation checklist includes:
- Detect new columns or categories that were not part of the expected schema. section 14.3.6
- Assert individual feature types, such as requiring a numerical value rather than an incorrectly formatted input. section 14.3.6
- Add range and domain checks, such as age below 100 or sensor readings between 10 and 12. section 14.3.6
A production safeguard
A monitoring policy can pause the model or use a fallback when critical inputs violate schema or quality checks, rather than silently serving unreliable predictions. section 14.3.6
