What Is Synthetic Data?

Synthetic data is generated by algorithms or models to resemble real records in shape, distribution, and relationships, but it contains no actual production information. Teams use it to populate test environments, train models, or share datasets without leaking personal or confidential data. It can be rule-based or sampled from a model fitted to real data.

Why it matters

Real production data is often restricted by privacy rules and is risky to copy into test systems. Synthetic data lets pipelines exercise realistic volumes and edge cases while keeping sensitive records out of lower environments.

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