Map what the test actually needs
List the fields, relationships, and behaviors required by the software test. Remove source fields that are unnecessary. A realistic name or a real address often contributes less to a regression test than a valid relationship between records.
Define constraints explicitly
Specify required formats, nullability, boundary values, and cross record rules. Include exceptional states that ordinary production samples are unlikely to contain. Focus on functional realism.
Treat synthetic data as data that needs review
Generation can preserve sensitive information if source usage and evaluation are poorly controlled. Review similarity, sensitive attributes, and access permissions. Synthetic does not automatically mean anonymous.
Keep a clear separation of environments
Agree on where source information may be processed and where generated records may be used. Define retention and deletion requirements for both. Confirm implementation details for the deployment before sharing sensitive material.
Document the handoff
Deliver the schema, scenario definitions, review findings, and use restrictions with the dataset. Teams should know which tests it supports and what conclusions it cannot justify.
Have a specific requirement? Book a meeting with RoboSynth to discuss your dataset and validation needs.