ARA-C01 Data Engineering Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Schedule a Task to query the VALIDATE_PIPE_LOAD function every hour

  Why it's wrong here

  While querying validation functions can identify errors, it is a polling-based approach that introduces latency. Architects prefer push-based notifications for production pipelines to ensure that issues are identified and remediated immediately, rather than waiting for the next scheduled task execution window.

• ✓

  Configure the ERROR_INTEGRATION parameter on the PIPE object

  Why this is correct

  Setting up an Error Integration allows Snowpipe to automatically send notifications to a cloud provider's messaging service (like AWS SNS, Azure Event Grid, or GCP Pub/Sub) whenever a load error occurs. This provides a proactive, near real-time alerting mechanism for data ingestion failures.

• ✗

  Use a Stream on the target table to track failed insert attempts

  Why it's wrong here

  Streams track successful DML changes (inserts, updates, deletes) in a table. They do not capture failed attempts or errors that prevented the data from being loaded in the first place. Therefore, a stream is an inappropriate tool for monitoring ingestion errors or pipeline health.

• ✗

  Set the Snowpipe parameter ON_ERROR = 'NOTIFY'

  Why it's wrong here

  There is no 'NOTIFY' value for the ON_ERROR parameter in Snowflake. The valid values are CONTINUE, SKIP_FILE, or ABORT_STATEMENT. Error notification is handled through a separate architectural component called an Error Integration, which is linked to the pipe's metadata.