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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 is using Snowflake Streams on a table 'TRANSACTIONS' to capture changes for auditing purposes. The 'TRANSACTIONS' table contains sensitive data, and the auditing team requires the stream to only capture changes to specific columns: 'ACCOUNT ID', 'TRANSACTION DATE', and 'TRANSACTION AMOUNT'. Which of the following approaches is the MOST efficient and secure way to achieve this requirement, ensuring minimal performance impact and data exposure?

A. Create a View that selects only the 'ACCOUNT ID, 'TRANSACTION DATE, and 'TRANSACTION AMOUNT columns and create a Stream on the View.
B. Create a Stream on the 'TRANSACTIONS' table and use a masking policy on the stream's output to redact the unnecessary columns.
C. Create a task that clones the TRANSACTIONS table and a stream on that cloned table, limiting what changes are captured using a WHERE clause on the cloning command.
D. Create a Stream on the 'TRANSACTIONS' table. Periodically truncate stream and reload all data from TRANSACTION table by applying filter while loading.
E. Create a standard Stream on the 'TRANSACTIONS table and then filter the results in downstream processing to only include the required columns.

Question 2

You have a Snowflake Stream named 'ORDERS STREAM' on an 'ORDERS' table, which is used to incrementally load data into a historical orders table named 'HISTORICAL ORDERS'. The data pipeline involves a series of tasks: 1) Consume changes from the 'ORDERS STREAM', 2) Apply transformations and data quality checks, and 3) Merge the changes into 'HISTORICAL ORDERS' using a MERGE statement. After a recent data load, you notice that the 'HISTORICAL ORDERS' table contains duplicate records for certain 'ORDER values. The MERGE statement uses 'ORDER ID' as the matching key. You have confirmed that the transformation logic is correct and idempotent. Examine the MERGE statement below. What could be causing the duplicates, given the context of Streams and incremental loading?

A. The stream is not configured to capture DELETE operations from the ORDERS table, causing records that should have been removed in HISTORICAL ORDERS to remain.
B. The MERGE statement is not correctly handling updates and deletes from the stream. The 'WHEN NOT MATCHED' and 'WHEN MATCHED' clauses are not mutually exclusive, leading to potential insertions of duplicate rows.
C. The 'ORDERS STREAM' is retaining historical data beyond the data retention period, causing older records to be re-processed.
D. The stream's or 'BEFORE clause is being used incorrectly, potentially rewinding the stream to an earlier point in time.
E. Multiple tasks are concurrently consuming from the same 'ORDERS STREAM' without proper coordination, causing records to be processed multiple times.

Question 3

You are designing a Snowflake data pipeline that continuously ingests clickstream dat a. You need to monitor the pipeline for latency and throughput, and trigger notifications if these metrics fall outside acceptable ranges. Which of the following combinations of Snowflake features and techniques would be MOST effective for achieving this goal?

A. Create a custom dashboard using a Bl tool that connects to Snowflake via JDBC/ODBC and visualizes data ingestion and processing metrics. Manually monitor the dashboard for anomalies.
B. Implement a combination of Snowflake Streams, Tasks, and external functions. Streams capture changes, Tasks process the changes, and external functions send notifications to a monitoring service when latency or throughput issues are detected.
C. Rely on Snowflake's default resource monitors to track warehouse usage. If warehouse usage exceeds a certain threshold, assume there are performance issues and send a notification.
D. Use Snowflake's 'QUERY_HISTORY view to track query execution times and implement a scheduled task that queries this view, calculates latency and throughput, and sends email notifications using Snowflake's built-in email integration if thresholds are exceeded.
E. Use Snowflake's Event Tables and Event Notifications to capture events related to data ingestion and processing. Configure alerts based on event patterns that indicate latency or throughput issues.

Question 4

You are implementing a data pipeline to load data from AWS S3 into Snowflake. The source data consists of CSV files with a header row. Some of the CSV files have inconsistent data types in a specific column (e.g., sometimes an integer, sometimes a string). You want to use the 'COPY' command to load the data and handle these data type inconsistencies gracefully. Which of the following 'COPY' command options, used in conjunction, would BEST address this issue and avoid load failures? Assume the file format is already defined to specify CSV type, header skip, and field delimiter.

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

Question 5

A critical database, 'PRODUCTION DB', in your Snowflake account was accidentally dropped. You need to restore it as quickly as possible, but you're unsure if Time Travel retention is sufficient. Which method guarantees restoration of the database even if it falls outside the Time Travel window?

A. Use the 'UNDROP DATABASE PRODUCTION command.
B. Utilize the data cloning feature: 'CREATE DATABASE CLONE PRODUCTION_DB BEFORE (STATEMENT 'DROP DATABASE PRODUCTION_DB');'
C. Fail-safe cannot be directly accessed by the user for restoration purposes; it is only used by Snowflake Support in extreme disaster recovery scenarios.
D. Contact Snowflake Support and request restoration from Fail-safe.
E. Restore from a Snowflake-managed backup using the 'CREATE DATABASE ... FROM BACKUP' command. Specify the timestamp before the drop occurred.

Solutions: