Built-in Privacy Protection by Design
Respecting user privacy – with technology made for it
At Scoby Analytics, privacy isn’t an added feature – it’s a fundamental part of the system. From architecture to implementation, our platform is designed to ensure that no individual can be identified, directly or indirectly.
We use privacy-preserving technologies (PETs) not as optional layers, but as core building blocks of our analytics model. The result: actionable data that remains fully anonymous and respectful of digital autonomy.
How Scoby protects privacy – by default
k-anonymity
Every data point is structurally indistinguishable from at least k-1 others. This ensures that no individual user can be isolated or identified within our datasets.Differential privacy
By introducing calibrated statistical noise, we make sure that no single data point can meaningfully influence the result – protecting user presence and absence alike.l-diversity
We enforce meaningful diversity across sensitive attributes to prevent inference attacks. This adds another layer of protection – especially in edge cases.
No raw data. No profiles. No risk.
Scoby Analytics does not generate or store raw, identifiable data. Everything is aggregated by design, meaning there is no way to trace patterns back to individuals – and nothing to export that could violate trust.
Instead of reconstructing user behavior, we deliver high-quality, collective usage insights – clear, consistent, and privacy-safe.
Get in touch to learn how Scoby helps you analyze responsibly – with privacy embedded into every layer of your analytics architecture.