Synthetic Data Fidelity

Synthetic data fidelity refers not just to whether generated data looks realistic, but whether it preserves similarity that is useful for analytics and modeling. Distributional alignment, correlation structure, marginal statistics, and downstream model performance may all be part of this evaluation. Without high fidelity, synthetic data may look convincing visually while remaining analytically weak. For that reason, quality assessment is just as important as generation in synthetic data projects.