What Is a Data Clean Room? Snowflake’s New Multi-Party Feature
What is a Snowflake Data Clean Room, and what’s new? In about a minute: how companies can combine data without sharing raw data, how the rules and differential privacy work, and why collaboration clean rooms matter. The older provider/consumer clean rooms are being retired in 2027: the web interface and new legacy rooms end on Feb 1, 2027, and legacy rooms stop working on Jun 1, 2027. Check the current Snowflake documentation for details. Follow for more Snowflake tutorials.
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A Data Clean Room is a secure environment where two or more companies can combine and analyze their data without directly sharing their raw, sensitive, or personally identifiable information.
It helps companies gain insights from shared data while protecting customer privacy and following data privacy regulations.
Example: Suppose Amazon and a clothing brand want to understand how many customers who viewed an advertisement later purchased clothes. They can use a data clean room to analyze overlapping customer data without exposing individual customer details to each other.
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Key benefits:
- Data privacy: Protects sensitive customer information.
- Secure collaboration: Allows companies to analyze combined datasets.
- Better insights: Helps with advertising effectiveness, customer behavior, and analytics.
- Access control: Uses permissions and privacy rules to control what users can analyze or retrieve.
Popular use cases: Advertising analytics, retail customer insights, financial services, and healthcare research.
