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

1. You have configured a replication group to replicate a database 'CUSTOMER DATA' from your primary Snowflake account (AWS us- east-I) to your secondary Snowflake account (Azure eastus). After a recent network outage, the replication process stopped. Upon investigation, you find that some tables in the 'CUSTOMER DATA' database in the primary account have been modified (schema changes). You need to resume replication and ensure data consistency in the secondary account, with minimal impact on users querying the secondary database. Which of the following commands or sequence of commands would be the MOST appropriate to refresh the secondary database while minimizing downtime for query users?

A) First, suspend the replication group with 'ALTER REPLICATION GROUP SUSPEND;'. Then, drop the secondary database 'DROP DATABASE . Finally, recreate the secondary database as a replica: 'CREATE DATABASE AS REPLICA OF and resume the replication group 'ALTER REPLICATION GROUP RESUME;'.
B) First, pause all running queries on the secondary account. Then, execute a full refresh using 'ALTER DATABASE REFRESH FROM Finally, resume the queries on the secondary account.
C) Suspend the replication group with 'ALTER REPLICATION GROUP SUSPEND;' Then execute the following: 'ALTER DATABASE ENABLE REPLICATION TO ACCOUNT ALTER REPLICATION GROUP RESUME;'
D) Issue a 'ALTER DATABASE REFRESH FROM command. This command automatically handles schema changes and ensures data consistency with minimal downtime.
E) Issue a 'ALTER REPLICATION GROUP REFRESH$ command. This will automatically handle schema changes and resume replication.

2. A data engineering team is responsible for processing a high volume of semi-structured JSON data ingested daily into Snowflake. The ingestion process currently uses a single 'X-Large' virtual warehouse. During peak hours, the data loading latency increases significantly, impacting downstream reporting. The team is considering either scaling up to a '3X-Large' warehouse or scaling out by creating a multi- cluster warehouse with a minimum of 2 and a maximum of 4 'X-Large' clusters. Which of the following factors should be prioritized when making this decision to optimize performance, considering cost and concurrency requirements?

A) The budget constraints and the higher per-second cost of a larger warehouse compared to the potential cost savings from reduced overall execution time.
B) The impact on other workloads sharing the same virtual warehouse, favoring scaling up to isolate the data loading process from other query activities.
C) The type of JSON processing used. If using SQL functions like PARSE JSON, scaling out is more beneficial than scaling up.
D) The complexity of the JSON data and the potential for improved parsing performance by a larger, single warehouse due to increased memory.
E) The anticipated number of concurrent data loading jobs and the ability of Snowflake to automatically distribute these jobs across multiple clusters.

3. You need to define a UDF in Snowflake that takes a date as input and returns the next business day (Monday-Friday). If the input date is a Friday, the UDF should return the following Monday. If the input date is a Saturday or Sunday, the function should return the following Monday as well. Which of the following UDF definitions correctly implements this logic?

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

4. 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?

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

5. You are implementing a data share between two Snowflake accounts. The provider account wants to grant the consumer account access to a function that returns anonymized customer data based on a complex algorithm. The provider wants to ensure that the consumer cannot see the underlying implementation details of the anonymization algorithm. Which of the following approaches can achieve this goal? (Select TWO)

A) Share the underlying table and provide the consumer account with the anonymization algorithm separately.
B) Create a secure UDF in the provider account and grant usage on the secure UDF to the share. Share the share with the consumer account.
C) Create a standard UDF in the provider account and grant usage on the UDF to the share. Share the share with the consumer account.
D) Create an external function in the provider account and grant usage to the share. Share the share with the consumer account.
E) Create a view that calls the secure UDF and share that view with the consumer account.

Solutions: