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Longer explanations for teams evaluating synthetic data: how the privacy math works, how to test what a vendor delivers, and when the whole approach is the wrong one.
Differential privacy in synthetic data, in plain English
Differential privacy in synthetic data explained without the math: what epsilon and delta mean, what they protect, what they cost and what to ask vendors.
How to test synthetic data quality: fidelity, utility and privacy
How to test synthetic data quality in a vendor trial: fidelity, utility and privacy checks to run, pass marks to agree first, and what reports leave out.
Synthetic tabular data or simulated images: different vendors for different jobs
Synthetic tabular data and simulated images come from different vendors with different methods, prices and tests. How to tell which one your project needs.
When synthetic data fails: four warning signs
When synthetic data fails it rarely crashes: it looks fine and misleads. Four warning signs to watch in a trial, how to test each, and what to do next.
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