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Snowflake DEA-C02 Exam Syllabus Topics:

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

Question 1

A financial services company stores sensitive customer data, including credit card numbers, in a Snowflake table called 'CUSTOMER DATA. You need to implement dynamic data masking on the 'CREDIT CARD NUMBER column. You want to ensure that only users with the FINANCE ADMIN' role can view the unmasked credit card numbers. All other users should see a masked version of the data'. Which of the following set of commands is the MOST efficient and secure way to achieve this?

A. Option A
B. Option D
C. Option B
D. Option E
E. Option C

Question 2

Consider a scenario where you're optimizing a data pipeline in Snowflake responsible for aggregating sales data from multiple regions. You've identified that the frequent full refreshes of the target aggregated table are causing significant performance overhead and resource consumption. Which strategies could be employed to optimize these full refreshes without sacrificing data accuracy?

A. Schedule the full refreshes during off-peak hours when the Snowflake warehouse is less utilized. This minimizes the impact on other workloads but does not reduce the actual processing time.
B. Replace the full refresh with a 'TRUNCATE TABLE' followed by an 'INSERT statement. This approach is faster than 'CREATE OR REPLACE TABLE' and reduces locking.
C. Implement incremental data loading using streams and tasks. This allows you to only process and load the changes that have occurred since the last refresh, reducing the amount of data that needs to be processed.
D. Leverage Snowflake's search optimization service on the base tables. While costly, this will dramatically speed up full table scans performed in the aggregation.
E. Utilize Snowflake's Time Travel feature to clone the previous version of the aggregated table, apply the necessary changes to the clone, and then swap the clone with the original table using 'ALTER TABLE SWAP WITH'. Note that this will impact data availability during the swap operation.

Question 3

You are tasked with building a data pipeline that incrementally loads data from an external cloud storage location (AWS S3) into a Snowflake table named 'SALES DATA'. You want to optimize the pipeline for cost and performance. Which combination of Snowflake features and configurations would be MOST efficient and cost-effective for this scenario, assuming the data volume is substantial and constantly growing?

A. Use a Snowflake Task scheduled every 5 minutes to execute a COPY INTO command from S3, with no file format specified, assuming the data is CSV and auto-detection will work.
B. Use a Snowflake Task to regularly truncate and reload 'SALES DATA" from S3 using COPY INTO. This ensures data consistency.
C. Develop a custom Python script that uses the Snowflake Connector for Python to connect to Snowflake and execute a COPY INTO command. Schedule the script to run on an EC2 instance using cron.
D. Create an external stage pointing to the S3 bucket. Create a Snowpipe with auto-ingest enabled, using an AWS SNS topic and SQS queue for event notifications. Configure the pipe with an error notification integration to monitor ingestion failures.
E. Employ a third-party ETL tool to extract data from S3, transform it, and load it into Snowflake using JDBC. Schedule the ETL process using the tool's built-in scheduler.

Question 4

You have a Snowflake table 'CUSTOMER DATA' with the following schema:

Your downstream application requires a new column 'PHONE NUMBER VARCHAR(20)' in the 'CUSTOMER DATA' table. You need to add this column without causing any downtime or disruption to the application. What is the MOST appropriate approach?

A. Create a new stream on the table 'CUSTOMER DATA'. Then, create a new table 'CUSTOMER DATA NEW' with the extra PHONE NUMBER column as part of the DDL. Use the stream and table to update data from the old to new table, Then, drop "CUSTOMER_DATA' , and rename to 'CUSTOMER DATA'.
B. create a temporary table which is a copy of CUSTOMER_DATA but with the additional column. swap the CUSTOMER_DATA and CUSTOMER DATA TEMP tables.
C. Create a new table 'CUSTOMER DATA NEW' with the new column, copy data from 'CUSTOMER DATA' to 'CUSTOMER DATA NEW, drop "CUSTOMER DATA', and rename 'CUSTOMER DATA NEW' to 'CUSTOMER DATA'.
D. Execute 'ALTER TABLE CUSTOMER DATAADD COLUMN PHONE NUMBER VARCHAR(20);'. This will add the column with a NULL value for existing rows.
E. Create a view 'CUSTOMER on top of 'CUSTOMER DATA' that includes the new 'PHONE NUMBER column with a default value. Update the application to use the view instead of the table.

Question 5

You are tasked with optimizing a data pipeline that loads data from an external cloud storage location into Snowflake, transforms it, and then loads it into reporting tables. The pipeline is experiencing intermittent performance issues. You want to proactively identify and address these issues. Which of the following monitoring techniques and Snowflake features would be MOST effective for continuous monitoring and performance optimization?

A. Implement custom logging and monitoring using Snowflake Scripting and User-Defined Functions (UDFs) to capture granular performance metrics at each stage of the pipeline and push notifications via external functions to a monitoring service.
B. Enable Snowflake's Auto-Suspend and Auto-Resume features on the warehouse. This is the most efficient way to manage resources and optimize costs, indirectly addressing performance concerns.
C. Focus exclusively on optimizing SQL queries and data transformations. Monitoring is unnecessary since Snowflake automatically handles performance optimization.
D. Utilize Snowflake's System Functions to periodically query performance views (e.g., 'QUERY_HISTORY, ' and write aggregated metrics to a dedicated monitoring table. Configure a scheduled task to generate alerts based on predefined thresholds.
E. Rely solely on Snowflake's default query history and resource monitors. These automatically track performance and usage, providing sufficient insight without additional configuration.

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