DAA-C01 Exam Dumps | You have a Snowflake table 'customer data' containing personally identifiable information (PII) such

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Question 18/151

You have a Snowflake table 'customer data' containing personally identifiable information (PII) such as customer names and addresses. You need to create a de-identified version of this table for analytical purposes, replacing the names and addresses with synthetic data, while preserving referential integrity with other tables that use the original customer IDs. Which combination of Snowflake features and techniques would you use to achieve this securely and efficiently?

A. Use Snowflake's data masking policies to dynamically mask the PII columns during query execution.

B. Create a new table with the de-identified data using a combination of Snowflake's HASH function for customer IDs, and a user-defined function (UDF) to generate synthetic names and addresses. Use secure data sharing to provide access to the de-identified table.

C. Export the 'customer_data' table to a local file, de-identify the data using an external scripting language (e.g., Python), and then import the de-identified data back into Snowflake.

D. Use Snowflake's external functions to call an external service that provides de-identification capabilities.

E. Create a view on top of the original table using Snowflake's masking policies and row-level security, allowing only specific users to see the de-identified data.

Correct Answer: B,D

Options B and D are the best choices. Option B directly addresses the need for a de-identified table by generating synthetic data and using HASH to preserve referential integrity. Secure data sharing provides controlled access. Option D uses external functions to leverage specialized de-identification services. Options A and E are useful for dynamic masking, but do not create a separate de-identified dataset and may still expose PII to authorized users. Option C involves exporting data, which increases the risk of data leakage and is less efficient.

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