Data Clean Rooms: The Future of Privacy-Compliant Data Collaboration

1. Collaboration Meets Compliance

As organisations grapple with increasingly stringent privacy and data protection laws, the concept of the Data Clean Room (“DCR“) has emerged as a transformative solution that enables collaboration without compromising compliance. From advertisers analysing campaign effectiveness to healthcare institutions conducting joint research, DCRs offer a structured way to generate insights while ensuring that personal data remains protected and inaccessible. They represent the intersection of data-driven innovation and privacy-by-design.

2. What Is a Data Clean Room

A Data Clean Room is a secure and governed digital environment that allows two or more entities to combine datasets, perform analysis, and extract only aggregated or anonymised outputs without disclosing raw data. Each participant retains ownership and control of its data, while the clean room enforces stringent access controls, defining who can query, what can be viewed, and what outputs can leave the environment.

In essence, a DCR functions as a closed and protected analytical space that enables shared insights while ensuring that individual identities remain safeguarded.

3. Uses and Importance

Data Clean Rooms have become integral to modern data ecosystems because they allow organisations to balance analytical depth with compliance and accountability. A few examples of such uses are:

• In advertising and marketing, they enable brands and publishers to measure campaign reach, audience overlap, or conversion rates without sharing identifiers.
• In retail and analytics, they allow retailers and payment networks to study spending trends and consumer behaviour securely.
• In healthcare and research, they provide a way for institutions to collaborate on clinical or epidemiological studies while protecting patient confidentiality.

Across industries, they make possible collaborations that would otherwise be restricted by law, regulation, or confidentiality obligations. By embedding governance and privacy safeguards into their design, DCRs help reduce regulatory exposure and promote ethical data use.

4. Key Characteristics

A well-architected DCR integrates both technical and contractual safeguards to uphold privacy-by-design principles. Its defining characteristics include strict data isolation, governed access based on defined roles, the use of privacy-enhancing technologies such as hashing and encryption, output controls to prevent re-identification, contractual clarity regarding roles and responsibilities, and comprehensive audit trails to demonstrate compliance.

These mechanisms make DCRs both technically robust and legally defensible under global privacy frameworks.

5. Treatment under the General Data Protection Regulation (“GDPR“)

While Data Clean Rooms are not exempt from GDPR, they can be lawful if properly designed and implemented. The focus must be on accountability and compliance by design rather than circumvention. Thus, they must not be treated as a loophole, and it is imperative that they are a structured way to meet GDPR’s expectations for accountability and privacy. This can be achieved through ensuring the following:

• Scope and lawful basis: Each participant must have a lawful basis under Article 6, i.e., consent, contract, or legitimate interests.
• Data minimisation and purpose limitation: Processing must also adhere to the principles of purpose limitation and data minimisation under Article 5, ensuring that only data strictly necessary for the defined purpose is used.
• Roles and accountability: Contracts must clarify roles and responsibilities of each Data Fiduciary / Controller, and it must be clear whether the parties are acting jointly or independently.
• Anonymisation and pseudonymisation: Data that is used within the DCR must be truly anonymised and not merely pseudonymised in order to fall outside the scope of the GDPR.
• Data Protection Impact Assessments and other safeguards: Given the potential risks, it is advisable to conduct a Data Protection Impact Assessment (DPIA) and implement safeguards such as encryption, deletion policies, and audit documentation.

When these measures are observed, DCRs can meet the GDPR’s expectations for accountability, proportionality, and privacy by design.

6. Treatment under Indian Law

Under India’s present and emerging privacy framework, DCRs may not have it as easy as they do under the GDPR.

• Under the Digital Personal Data Protection Act, 2023, processing within a DCR may be exempt if interpreted as falling within the exemptions provided for in Section 17(2)(b) that states:

         “The provisions of this Act shall not apply in respect of the processing of personal data necessary for research, archiving or statistical purposes if the personal data is not to be used to take any decision specific to a Data Principal and such processing is carried on in accordance with such standards as may be prescribed.”

However, being a consent heavy legislation, the only alternative available in case of an interpretation to the contrary is for companies to ensure that the data being contributed to the DCR is already anonymised before submission which heavily reduces the ease and usability of these platforms.

• Additionally, under the Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011, if the data falls within the category of Sensitive Personal Data or Information organisations may still be required to obtain consent. Thus, the use of DCRs may be limited to data that does not fall within that category.

7. What to Look Out For

Organisations implementing or participating in a DCR should pay attention to a few critical elements. These include ensuring clear role definition and accountability, establishing a lawful basis and clearly documented purpose, addressing cross-border data transfers, enforcing output and access controls, providing audit and monitoring rights, defining retention and deletion periods, and continually assessing re-identification risks.

Attention to these factors ensures that the DCR operates as a privacy-enhancing mechanism rather than a compliance loophole.

8. Conclusion

As privacy regimes around the world evolve from data maximisation to data stewardship, the clean room stands as the future of responsible data collaboration. Data Clean Rooms must not be treated as a means to bypass regulation but rather an embodiment of compliance through design. When implemented correctly, they reflect the principles of minimisation, purpose limitation, and accountability.