Learn how to address the challenges organizations face that prevent unlocking critical business insights and performing analytics and machine-learning on sensitive data, including:
- Restricted data access to sensitive and confidential data
- Separation of data into sensitive data sets versus non-sensitive data sets
- Tedious, time-consuming masking of data fields
- Prevention of sensitive data sharing, restricting collaborative analytics
- Performing large-scale analytics and machine-learning on encrypted data
The Result: $300 billion worth of data remains untapped. Use cases from money laundering, to drug research, to audience monetization and more are complex. Time-critical business insights are taking 6-12 months to achieve. Hard-to-find security experts is an even bigger barrier.
Hear from Opaque and Intel, the pioneers of Confidential Computing and Confidential AI about:
- End-to-end Security from sourcing disparate data and protecting it in use.
- Encrypting data at rest, processing encrypted data in transit, and protecting data in use.
- Collaborative analytics and machine learning on encrypted data and governing access to insights.
- Governed data sharing and establishing policies when performing analytics.
- Use Cases across Banking, Insurance, AdTech, Drug Research, Healthcare, Media/Telecom and more.