Robust testing needs realistic data—minus the risk. Build pipelines that subset production tables to representative, right-sized samples while preserving referential integrity and edge cases. Mask or tokenize sensitive fields, and generate synthetic records to cover rare scenarios, boundary values, and error paths. Track coverage with metrics tied to user journeys and business rules, not just code lines. Version datasets alongside application releases so tests are repeatable, and refresh them automatically as schemas evolve. Self-service portals let teams request domain packs (e.g., customers, orders, payments) with clear SLAs. Together, these practices deliver faster cycles, fewer escapes, and audit-ready evidence that non-production environments remain compliant.