Snowflake - Build and Architect Data Pipelines Using AWS - Lab – End-to-End Pipeline in Action

What is the purpose of truncating tables before starting the data ingestion process?

• To clear any existing data and start fresh

• To improve data processing speed

• To ensure data is not duplicated

• To reduce storage costs

What is the main function of the Snowpipe object in the data ingestion process?

• To automate data ingestion

• To store data temporarily

• To analyze data

• To visualize data

Why is it important to set a prefix when creating an event notification in S3?

• To increase the speed of data transfer

• To avoid triggering Snowpipe for unrelated files

• To ensure notifications are sent for all files

• To reduce the cost of notifications

What is the role of SQS in the data ingestion process?

• To store data

• To trigger Snowpipe

• To analyze data

• To visualize data

What happens after a JSON file is uploaded to the S3 bucket?

• The file is deleted

• The data is manually moved to the production table

• The data is automatically ingested into the raw and production tables

• The data is archived

How can you verify that Snowpipe has successfully ingested data?

• By checking the S3 bucket

• By running a SQL command to view the data in the tables

• By checking the data processing speed

• By looking at the file size

What indicates that the Snowpipe was triggered successfully?

• The system shuts down

• Rows appear in the raw and production tables

• The data remains in the S3 bucket

• An error message appears