Snowflake SnowPro Advanced: Data Engineer (DEA-C02) : DEA-C02 valid dump torrent

You are tasked with implementing a projection policy in Snowflake to restrict access to certain columns of the 'EMPLOYEE table based on the user's role. The table contains columns like 'EMPLOYEE 'NAME, 'SALARY', and 'DEPARTMENT. Users with the 'HR MANAGER role should have access to all columns, while other users should only be able to see 'EMPLOYEE ID, 'NAME, and DEPARTMENT. The initial attempt to create the projection policy results in an error. What could be the reasons?

• A. The EMPLOYEE table must have row-level security policies enabled before applying a projection policy.
• B. The projection policy definition might contain syntax errors or reference non-existent roles or columns.
• C. Projection policies can only be applied at the database level, not at the table level.
• D. Projection policies are not supported in Snowflake.
• E. The user attempting to create the projection policy does not have the 'OWNERSHIP' privilege on the 'EMPLOYEE table.

You are building a data pipeline using Snowflake Tasks to orchestrate a series of transformations. One of the tasks, 'task _ transform data', depends on the successful completion of another task, 'task extract_data'. However, occasionally fails due to transient network issues. You want to implement a retry mechanism for 'task_extract data' without impacting the overall pipeline execution time significantly. Which of the following approaches is the most appropriate and efficient way to achieve this within the Snowflake Task framework?

• A. Use the 'AFTER keyword in the 'CREATE TASK' statement for 'task_transform_data' to only execute if succeeds on its first attempt. If fails, the entire pipeline will stop, ensuring data consistency.
• B. Configure the task with an error notification integration that sends alerts upon failure. Manually monitor these alerts and manually resume the task if it fails. Use 'ALTER TASK task extract data RESUME;'
• C. Implement a TRY...CATCH block within the task definition to catch any exceptions. Inside the CATCH block, use SYSTEM$WAIT to pause for a few seconds, then re- execute the core logic of the task. Repeat this process a limited number of times before failing the task permanently.
• D. Create a new root-level task that checks the status of 'task_extract_data'. If it failed, the root-level task will execute a copy of the 'task_extract data' task. After this, it updates the 'task_transform_data"s 'AFTER' condition to depend on the new task that retries extraction.
• E. Modify the task definition to call a stored procedure. The stored procedure implements a loop with a retry counter. Inside the loop, execute the data extraction logic. If an error occurs, catch the exception, wait for a few seconds, and retry the extraction. After a specified number of retries, raise an exception to signal task failure.

You have configured a Snowpipe to load data from an AWS S3 bucket into a Snowflake table. The data in S3 is updated frequently. You've noticed that despite the Snowpipe being active and the S3 event notifications being configured correctly, some newly added files are not being picked up by the Snowpipe. You run 'SYSTEM$PIPE and see the 'executionstate' is 'RUNNING' but the 'pendingFileCount' remains at O, even after new files are placed in the S3 bucket. Choose all of the reasons that could explain the observations.

• A. The IAM role associated with your Snowflake account does not have sufficient permissions to read from the S3 bucket. Specifically, it lacks the 's3:GetObject' permission.
• B. The file format specified in the Snowpipe definition does not match the actual format of the files being placed in the S3 bucket.
• C. There is an insufficient warehouse size configured for the Snowpipe. Increase the warehouse size for optimal performance.
• D. The SQS queue or SNS topic associated with the S3 event notifications has a message retention period that is too short. Messages containing event details for new files are being deleted before Snowpipe can process them.
• E. The S3 event notification configuration is missing the 's3:ObjectCreated: event type, meaning that new file creation events are not being sent to the SQS queue or SNS topic.

You are developing a data pipeline in Snowflake that processes sensitive customer data'. You need to implement robust data governance controls, including column-level security and data masking. Which of the following combinations of Snowflake features, when used together, provides the MOST comprehensive solution for achieving this?

• A. Dynamic tables and masking policies.
• B. Row-level security policies and data masking policies.
• C. Data masking policies and network policies.
• D. Object tagging, column-level security policies (using views), and masking policies.
• E. Row access policies and data masking policies on base tables, supplemented with object tagging and column-level security policies on views that grant limited access to specific user roles.

A data engineer is investigating high credit consumption on a Snowflake warehouse due to frequent re-clustering operations on a large table named 'WEB EVENTS. This table is clustered on 'EVENT TIMESTAMP' and 'USER ID. The engineer suspects that the high frequency of data ingestion, especially out-of-order 'EVENT TIMESTAMP' values, contributes to the poor clustering. Choose the options that can lead to optimizing clustering and reducing credit consumption, assuming you have limited control over the ingestion process and data quality.

• A. Implement a pre-processing stage to sort the incoming data by 'EVENT TIMESTAMP before loading it into the 'WEB EVENTS table, using a temporary table and then inserting into the final table.
• B. Implement a maintenance task to periodically re-cluster the table less frequently, but at more strategically chosen times (e.g., during off-peak hours).
• C. Drop the clustering key altogether to avoid re-clustering costs.
• D. Partition the table based on "EVENT _ TIMESTAMP' instead of clustering.
• E. Increase the warehouse size to accelerate the re-clustering process.