Data Validation
What is Data Validation?
Validation is the gate that stops bad data from entering the database. Rules range from simple (email matches a regex, country code is in the ISO list) to complex (this combination of fields is internally consistent, this foreign key exists in the referenced table). The most valuable place to validate is at entry — form-level validation, API-level validation, ingest-level validation — because catching errors there prevents them from corrupting downstream workflows. Modern validation increasingly uses AI for soft checks (does this title look real for this industry? does this company name match this domain?) on top of rule-based hard checks. The result is a database where the data that's in it is data you can act on.
Why it matters
- Stops bad data at the gate — far cheaper than fixing it after it's corrupted ten downstream systems.
- Improves form-fill rates when paired with real-time feedback — users fix issues before submitting.
- Makes the contract between systems enforceable — invalid records get rejected, not silently absorbed.
Use cases
- Form-level validation. Emails verified for format and deliverability before submission.
- API-level validation. Incoming integration payloads validated against schema before write.
- Cross-field validation. Checks that ZIP matches state, country matches phone country code, etc.
How turgo helps
turgo validates at every ingress — forms, API, batch import — and rejects malformed records with explicit error messages rather than absorbing them silently and corrupting downstream workflows.
See turgo in action →
