What are Snowflake Data Clean Rooms and what privacy problems do they solve?

Data Clean Rooms (DCRs) are privacy-preserving environments where two or more parties can run collaborative analytics on a union of their datasets without either party being able to see the other's raw records. Snowflake implements Clean Rooms on top of Secure Data Sharing and the Native App Framework.

The privacy problem they solve: an advertiser wants to measure how many of their customers saw a publisher's ad and subsequently made a purchase. This requires matching two customer lists. But the advertiser cannot share its customer list with the publisher and vice versa — both contain sensitive PII. A DCR lets them run the overlap-and-attribution query without either side ever getting a plain-text view of the other's underlying customer records.

Snowflake's Clean Room architecture enforces privacy through:

• Pre-approved query templates — only specific, vetted SQL queries may be executed; no ad-hoc access.
• Aggregation thresholds — results are suppressed if the matching cohort is smaller than a minimum size (e.g., <500 rows), preventing re-identification.
• No raw data export — results are returned as aggregates; the underlying rows are never exposed.
• Differential privacy options — statistical noise can be added to outputs to provide provable privacy guarantees.

Use cases span advertising (media measurement, audience activation), financial services (transaction reconciliation between banks), and healthcare (de-identified outcomes research across payer and provider datasets).