May 16, 2023

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What are data clean rooms

A data clean room is a secure environment where organizations can share and analyze data without compromising consumer privacy or corporate security. This controlled environment allows companies that would benefit from collaboration to aggregate their data and enable the incorporation of first-party data into the platform. By aggregating the data in a clean room, individual customer data is anonymized and consolidated to prevent identifying consumers. This provides a privacy-safe, secure and governed way for companies to collaborate on data analysis while maintaining a clear boundary that does not compromise competitive advantage or corporate strategies. The clean room ensures that all data used for collaboration is accurate, up-to-date and of high quality. 

Conventional clean rooms 

Data clean rooms have proven to be a valuable tool in marketing by refining customer segmentation, enriching campaign planning and helping build robust recommendation engines. With a clean room, companies can pool their data without revealing individual customer information creating a more complete view of the customer journey. For example, this allows for more effective segmentation based on demographics, interests, behaviors and more. Using this information, marketers can design more targeted campaigns with personalized messaging and product recommendations. All these benefits contribute to better customer experiences, higher engagement and increased revenue for businesses. 

New possibilities

Data clean rooms are not limited to just marketing. New trends such as distributed data clean rooms in Snowflake integration with Unified ID 2.0 and abilities to privately enrich data with LiveRamp or Experian data and frameworks are driving value in other industries and use cases. Manufacturing companies can use data clean rooms to optimize their supply chain operations by analyzing data from multiple sources to identify inefficiencies and opportunities for improvement. Direct-to-consumer companies can gain a deeper understanding of their customers by analyzing data in a secure environment, which can help improve the overall customer experience. Even Google is investing in clean rooms as they recently released new clean room capabilities within BigQuery  in a partnership with L’Oréal and Habu to better understand customers and the impact of business decisions (Gaekwad & Soares, 2023).

In healthcare, for example, data clean rooms could be used in the analysis of medical records for research and drug development to increase collaboration, security and governance. Medical records contain sensitive information and must be handled with care to protect patient privacy. A data clean room could be set up to allow researchers and pharmaceutical companies to access aggregate medical data while ensuring patient anonymity and complying with data privacy regulations. Historically this was accomplished through a lengthy, complex process of anonymization and de-identification using specialized tools to transfer large data files back and forth. The speed and efficiency of clean rooms provide instantaneous data and additional protections like consent, query approval/denial and historical lineage. Leveraging a modern clean room could facilitate the development of new treatments and medications by providing insights into patient characteristics and treatment outcomes at a pace not seen before. The use of data clean rooms in healthcare could lead to more accurate diagnoses, improved treatments and better patient outcomes while maintaining privacy and protection, and using data ethically. 


Data clean rooms provide a secure and controlled environment for data analysis, unlocking new insights and opportunities for businesses across various industries. From manufacturing to retail, data clean rooms can help many achieve value. Contact Nortal today to learn more about how data clean rooms can benefit your organization.


Source: Gaekwad, N., & Soares, A. (2023, March 29). Introducing bigquery data clean rooms | google cloud blog. Google.

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