COF-C03 Question 338
Single answerData clean roomsA retail company wants to collaborate with an advertising partner to measure campaign effectiveness using overlapping customer data, but neither party is allowed to expose raw personally identifiable information (PII) to the other. The data engineering team is evaluating Snowflake Data Clean Rooms for this use case. Which approach best meets the requirement while preserving privacy?
- A
Load both parties' raw customer tables into a shared database and grant SELECT access only to approved analysts
- B
Use a Snowflake Data Clean Room so each party keeps its data in its own environment and only approved analyses and policy-controlled results are shared
- C
Export both datasets to external cloud storage, hash the email addresses, and let the partner run joins outside Snowflake
- D
Create a secure data share of the raw customer table and rely on masking policies to prevent all possible re-identification risks
Show answer and explanation
Correct answer: B
Explanation
The best answer is to use a Snowflake Data Clean Room, which is intended for situations where organizations need to collaborate on sensitive data without directly exchanging raw records. This is a practical fit for advertising measurement, audience overlap, and similar partner analytics use cases. In Snowflake, the clean room approach focuses on controlled collaboration, privacy-preserving analysis patterns, and policy-based restrictions on what can be queried and returned. By contrast, directly sharing raw tables or exporting data outside Snowflake undermines privacy and governance objectives. Candidates should recognize that Data Clean Rooms are not simply another form of database sharing; they are specifically designed to enable governed collaboration while limiting exposure of sensitive data. This aligns with Snowflake guidance around secure data collaboration and the purpose of Data Clean Rooms.
- A. Incorrect.
This is incorrect because loading both parties' raw customer data into a shared database increases exposure of sensitive data and does not align with the core privacy-preserving design of clean rooms. Even if access is limited to approved analysts, the raw data is still being directly shared, which violates the stated requirement that neither party expose raw PII to the other.
- B. Correct.
This is correct. Snowflake Data Clean Rooms are designed for privacy-enhanced collaboration where participants can analyze overlapping datasets without directly revealing raw underlying data to one another. The clean room model emphasizes governed collaboration, approved analysis templates or controls, and restricted result sharing, which fits the campaign measurement scenario.
- C. Incorrect.
This is incorrect because moving data outside Snowflake to external storage weakens governance, auditing, and security controls. Hashing email addresses alone is not a sufficient privacy guarantee, especially if the same hashing method can still allow deterministic matching and potential re-identification. This option also bypasses the clean room capabilities intended for controlled collaboration.
- D. Incorrect.
This is incorrect because a secure data share of the raw customer table still exposes the underlying shared dataset to the recipient account, subject to granted permissions. While masking policies can help protect sensitive fields in some scenarios, they are not the same as a clean room approach and do not by themselves provide the governed, analysis-centric collaboration model required here.