GDPR-Safe Test Data
You can't put real personal data in test, demo, or training environments — but you still need data that behaves like real people. Synthetic data settles this cleanly: SimpleIDGen generates records from public reference distributions, so there is no personal data to protect in the first place. Nothing is learned from, or traceable to, a real individual.
No signup. Generate your own — 5,000 rows/day free →
Masking and anonymization start from real records and try to obscure them — but the rows still descend from real people, and re-identification risk never fully disappears, especially once datasets are joined. Under the EU GDPR and India's DPDP, such data can remain "personal data," with all the obligations that follow.
Synthetic data has no such lineage. SimpleIDGen never ingests a real dataset; it samples each attribute from a published distribution and assembles fresh records. There is no data subject behind any row, so the personal-data obligations don't attach in the first place. (As always, confirm your specific use with your own compliance team.)
| Property | What it means for compliance |
|---|---|
| No real source data | Built from public US references (NHANES, ACS, CDC, KFF) — not learned from real records. |
| No personal data | No row corresponds to a real individual; there is nothing to re-identify. |
| Calibrated, not random | Distributions match a real population, so the data is useful for realistic testing. |
| Deterministic | Same seed yields the same data, so environments stay reproducible. |
| Yours to keep | CSV / JSONL you can store, share, and pipe anywhere — no PII-handling rules to inherit. |
Filling non-production databases (dev, staging, QA) without copying production PII; product demos and sales sandboxes; sharing realistic datasets with vendors, contractors, or offshore teams; and training or evaluating models where regulated data can't be used. The synthetic patient data → set covers healthcare-shaped needs specifically.
No. Every record is generated from public reference distributions. No real dataset is ingested and no row maps to a real person.
Because the data isn't personal data, the personal-data obligations of the GDPR and DPDP don't attach to it. That's a property of synthetic data, not legal advice — confirm your specific scenario with your compliance team.
It contains no protected health information by construction, which is why teams use it where production patient data can't be. Again, check with your compliance officer for your case.
Yes. Since there's no personal data, you can store, share, and distribute the generated files without inheriting PII-handling obligations.