A training pipeline must validate required columns and numeric ranges before starting an expensive job. Which design is best?

1. Silently replace every invalid column with zeros without approval.
2. Delete validation rules whenever a source changes unexpectedly.
3. Start training first and inspect only the final model filename.
4. Run explicit schema and data-quality checks in preprocessing and stop on invalid required inputs.