Privacy-Preserving Analytics
Enable organizations to analyze sensitive data securely using techniques like federated learning and differential privacy. This allows compliance with data protection laws while still extracting valuable insights.
Example Case Study: Secure Health Data Analysis
A health tech firm wants to analyze patient data across multiple clinics without compromising privacy. Using federated learning, they train models locally at each clinic and aggregate results without sharing raw data.
This approach ensures compliance with data protection laws like GDPR and HIPAA. Clinics benefit from shared insights while maintaining control over their sensitive data.