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Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions:

1. You are tasked with sharing a subset of a customer table (CUSTOMER DATA') residing in your organization's Snowflake account with a partner organization. You need to mask personally identifiable information (PII) while providing near real-time updates. You decide to use a secure view. Which of the following SQL statements is the MOST efficient and secure way to accomplish this, assuming the partner only needs 'customer id', 'masked_email', 'city', and 'state'? The email should be masked using SHA256.

A) Option C
B) Option A
C) Option B
D) Option D
E) Option E

2. Which of the following statements are true regarding using Dynamic Data Masking and Column-Level Security in Snowflake? (Select all that apply)

A) Dynamic Data Masking policies can reference external tables directly without requiring special grants.
B) Column-Level Security via views provides more fine-grained control over data access compared to Dynamic Data Masking.
C) Dynamic Data Masking can be used to apply different masking rules based on the user's role, IP address, or other contextual factors.
D) Using both Dynamic Data Masking and Column-Level Security (e.g. views) on the same column is redundant and will result in an error.
E) Dynamic Data Masking is applied at query runtime, while Column-Level Security through views or roles is applied when the object is created.

3. You have a complex data pipeline implemented using Snow park Python. The pipeline involves multiple Data Frame transformations, joins, aggregations, and window functions. To enhance the maintainability and readability of the code, you want to modularize the pipeline into reusable functions. You also need to handle potential errors and exceptions gracefully. Consider the following code snippet:

A)

B)

C)

D)

4. You are using Snowpipe to ingest data from Azure Blob Storage into a Snowflake table. You have successfully set up the pipe and configured the event notifications. However, you notice that duplicate records are appearing in your target table. After reviewing the logs, you determine that the same file is being processed multiple times by Snowpipe. Which of the following strategies can you implement to prevent duplicate data ingestion, assuming you cannot modify the source data in Azure Blob Storage to include a unique ID or timestamp?

A) Use a data masking policy with the 'MASK' function to obfuscate duplicate records based on their similarity, making them effectively invisible to downstream queries.
B) Modify the Azure Event Grid subscription configuration to filter events based on file size or creation time to avoid resending events for already processed files.
C) Create a Snowflake stream on the target table and use it to incrementally load data into a separate, deduplicated table using a merge statement with conditional logic to insert or update records based on a combination of columns.
D) Configure the Snowpipe definition with the 'PURGE = TRUE parameter. This will ensure that each file is only processed once.
E) Implement idempotent logic within a Snowflake stored procedure that is triggered by a task after the data is loaded by Snowpipe. The stored procedure should identify and remove duplicate rows based on all other columns in the table.

5. You need to implement both a row access policy and a dynamic data masking policy on the 'EMPLOYEE table in Snowflake. The requirements are as follows: 1. Employees should only be able to see their own record in the 'EMPLOYEE table. 2. The 'SALARY' column should be masked for all employees except those with the 'HR ADMIN' role. Unmasked values are required for compliance reasons, they need to be available for 'HR ADMIN' role. Given the following table structure: CREATE TABLE EMPLOYEE ( EMPLOYEE ID INT, EMPLOYEE NAME STRING, SALARY NUMBER, EMAIL STRING ) ; Which of the following sets of steps correctly implement the row access policy and dynamic data masking policy?