Good use cases
- Load and integration testing.
- Testing rare error paths.
- Prototyping a schema before production data is available.
- Balancing a known class imbalance for exploration.
- Sharing examples across teams without exposing customer records.
When it is a bad substitute
Synthetic data cannot prove that a system works on real users when it does not preserve the messy relationships, language, missing fields, and rare events found in production. Keep a protected real-world test set for final evaluation.
The decision test
Can you state what the synthetic data must preserve and what it is allowed to simplify? Can you test for memorization, bias, and distribution drift? If not, use synthetic data only for low-risk development until the validation plan exists.