Snowflake - Build and Architect Data Pipelines Using AWS - Lab - Ingest CSV from S3 to Snowflake

The video tutorial guides viewers through setting up roles and schemas in Snowflake, creating a line item table, defining a file format for data ingestion, and creating a stage object for loading data from S3. It also covers the process of ingesting CSV data into the table, including error handling and verifying the data load.

What is the first step in setting up the Snowflake environment for data ingestion?

• Creating a new user

• Uploading data files

• Switching to the Sysadmin role

• Creating a new database

Why is it important to create a file format in Snowflake?

• To manage user permissions

• To automate data backups

• To specify how data files are interpreted

• To define the structure of the database

What is the purpose of a stage object in Snowflake?

• To specify the location of data files

• To manage database connections

• To define user roles

• To create a new schema

Which command is used to list the contents of a stage object?

• LIST @stage_name

• SHOW STAGE

• SELECT * FROM stage_name

• DESCRIBE STAGE

What does the 'on error' option do during data ingestion?

• It stops the execution if an error occurs

• It ignores the error and proceeds

• It retries the failed operation

• It logs the error and continues

How can you verify that all data files were successfully ingested?

• By reviewing the error logs

• By checking the number of rows loaded

• By running a SELECT query

• By comparing file sizes

What should you do if a data file fails to load during ingestion?

• Use the 'continue' option to skip the file

• Manually edit the file

• Retry the ingestion process

• Delete the file and try again