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

1. You have a requirement to continuously load data from a cloud storage location into a Snowflake table. The source data is in Avro format and is being appended to the cloud storage location frequently. You want to automate this process using Snowpipe. You've already created the Snowpipe and the associated stage and file format. However, you notice that some files are being skipped during the ingestion process, and data is missing in your Snowflake table. What is the MOST likely reason for this issue, assuming all necessary permissions and configurations (stage, file format, pipe definition) are correctly set up?

A) The Snowpipe is paused due to exceeding the daily quota.
B) The data files in cloud storage are not being automatically detected by Snowpipe.
C) Snowflake does not support Avro format for Snowpipe.
D) The file format definition in Snowflake is incompatible with the Avro schema.
E) The cloud storage event notifications are not properly configured to trigger Snowpipe.

2. 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 Stream on the 'TRANSACTIONS' table. Periodically truncate stream and reload all data from TRANSACTION table by applying filter while loading.
B) Create a View that selects only the 'ACCOUNT ID, 'TRANSACTION DATE, and 'TRANSACTION AMOUNT columns and create a Stream on the View.
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 and use a masking policy on the stream's output to redact the unnecessary columns.
E) Create a standard Stream on the 'TRANSACTIONS table and then filter the results in downstream processing to only include the required columns.

3. Consider a table with columns and 'customer _ region'. You want to implement both a Row Access Policy (RAP) and an Aggregation Policy on this table. The RAP should restrict access to orders based on the user's region, defined in a session variable 'CURRENT REGION'. Users should only see orders from their region. The Aggregation Policy should mask order totals for regions other than the user's region when aggregating data'. In other words if someone attempts to aggregate ALL region's totals, the aggregation will only include their region. Which statements about implementing this scenario are true?

A) You can use the function within both the RAP and Aggregation Policy to control access based on user roles in addition to region.
B) You cannot use session variables directly in Row Access Policies; you must pass the session variable as an argument to a user-defined function (UDF) called by the policy.
C) The Aggregation Policy is evaluated before the RAP, ensuring that even if users try to bypass the RAP by aggregating across all regions, the results will be masked appropriately according to 'CURRENT REGION'.
D) Using external functions in RAPs can introduce performance overhead, especially if the external function is complex or slow to execute.
E) The RAP should be applied first to filter the data, and then the Aggregation Policy will apply to the filtered data, only masking aggregated values within the user's region.

4. 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) Issue a 'ALTER REPLICATION GROUP REFRESH$ command. This will automatically handle schema changes and resume replication.
B) Suspend the replication group with 'ALTER REPLICATION GROUP SUSPEND;' Then execute the following: 'ALTER DATABASE ENABLE REPLICATION TO ACCOUNT ALTER REPLICATION GROUP RESUME;'
C) 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.
D) Issue a 'ALTER DATABASE REFRESH FROM command. This command automatically handles schema changes and ensures data consistency with minimal downtime.
E) 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;'.

5. You are designing a data pipeline that involves unloading large amounts of data (hundreds of terabytes) from Snowflake to AWS S3 for archival purposes. To optimize cost and performance, which of the following strategies should you consider? (Select ALL that apply)

A) Enable client-side encryption with KMS in S3 and specify the encryption key in the 'COPY INTO' command to enhance security.
B) Use a large Snowflake warehouse size to parallelize the unload operation and reduce the overall unload time.
C) Partition the data during the unload operation based on a high-cardinality column to maximize parallelism in S3.
D) Choose a file format such as Parquet or ORC with compression enabled to reduce storage costs and improve query performance in S3.
E) Utilize the 'MAX FILE SIZE parameter in the 'COPY INTO' command to control the size of individual files unloaded to S3. Smaller files generally improve query performance in S3.

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