The Gartner Data and Analytics Summit 2022 in Orlando highlighted various trends and challenges in the data industry, with a significant focus on synthetic data and its role in training models without exposing real data to risks. However, the event notably lacked discussions on data collaboration, a crucial element for overcoming data silos and enabling secure, privacy-preserving data sharing. The misconception that synthetic data alone can address secure data collaboration needs suggests a gap in understanding Privacy Enhancing Technologies (PETs), which could potentially solve these issues. The Duality privacy-preserving collaboration platform was presented as a solution for applying models to sensitive data without exposing it, facilitating cross-departmental and cross-border collaboration. The platform's ability to securely link multiple real data sets using post-quantum encryption offers enterprises a chance to unify data previously constrained by privacy limitations. This approach not only protects sensitive data but also safeguards proprietary models, enhancing monetization opportunities. Despite the promise of PETs in breaking down data silos, there remains skepticism about their practicality, likening them to science fiction. However, the Duality Platform demonstrates the potential to unlock valuable insights from sensitive data while maintaining privacy.