Data clean rooms are becoming essential tools for organizations engaged in data-driven activities, offering a way to collaborate on data while maintaining privacy and compliance with regulations like GDPR and CCPA. These platforms enable businesses to share insights without exposing their first-party data, providing advantages such as control over data and the ability to perform versatile analyses using programming languages like Python and SQL. However, they also present challenges, including less accurate outputs due to data aggregation, privacy risks from potential breaches, and the complexity of working with different data formats. Additionally, the reluctance of some parties to share data and the non-interoperability of many clean rooms can limit their effectiveness. Despite these drawbacks, data clean rooms are seen as a potential solution for maintaining privacy in data collaboration, as companies seek holistic platforms that integrate multiple privacy-enhancing technologies to meet evolving privacy standards and business needs.