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.