Managing data governance becomes easy. No need to assess risk and revisit anonymization strategies every single time. Privacy policies scale to all data needs with maximum compliance.
Starting data projects has never been easier. Create insights, build models and ship code without depending on engineering or compliance approvals. Work on original data with all BI tools and standard ML libraries.
Stop implementing and maintaining complex anonymization logic for every analytics and data science need. No need to worry about sensitive data copies.
Get the finest control over data access by leveraging the latest privacy research.
Automated generation of high utility samples for preparatory work and high level analyses.
Use Sarus Privacy-first Gateway to interact with the original data asset in privacy-preserving manner.
A full suite of libraries and integrations to weave privacy into existing workflows.
Apple has adopted and further developed a technique known in the academic world as local differential privacy to do something really exciting: gain insight into what many Apple users are doing, while helping to preserve the privacy of individual users.
Differential privacy simultaneously enables researchers and analysts to extract useful insights from datasets containing personal information and offers stronger privacy protections.
2020 US Census results will be protected using differential privacy, the new gold standard in data privacy protection.