* Alerts in Snowflake are schema-level objects that allow users to define conditions and actions to be performed automatically when those conditions are met.
* Alerts use a schedule to periodically evaluate a query result and take action if the condition evaluates to TRUE.
Example:
CREATE ALERT my_alert
IF (SELECT COUNT(*) FROM my_table WHERE status = 'ERROR') > 0
SCHEDULE = '5 MINUTE'
ACTION = CALL notify_error_procedure();
Why Other Options Are Incorrect:
* B. External tables: Used to query external data but cannot trigger actions.
* C. Secure views: Ensure data privacy but do not perform actions.
* D. Materialized views: Improve performance by precomputing query results but do not perform periodic actions.
References:
* Snowflake Alerts Documentation

Temporary tables in Snowflake do not consume storage costs. They are designed for transient data that is needed only for the duration of a session. Data stored in temporary tables is held in the virtual warehouse's cache and does not persist beyond the session's lifetime, thereby not incurring any storage charges.
References:
* Snowflake Documentation: Temporary Tables

To upload data files from a local directory or folder on a client machine to an internal stage in Snowflake, the PUT command is used. The PUT command takes files from the local file system and uploads them to an internal Snowflake stage (or a specified stage) for the purpose of preparing the data to be loaded into Snowflake tables.
Syntax Example:
PUT file://<local_file_path> @<stage_name>;
This command is crucial for data ingestion workflows in Snowflake, especially when preparing to load data using the COPY INTO command.
Reference: Snowflake Documentation on Using the PUT Command: https://docs.snowflake.com/en/sql- reference/sql/put.html

A VARIANT column in Snowflake is specifically designed to store semi-structured data, such as JSON, and allows for the creation of a data hierarchy. Unlike string columns, VARIANT columns can natively handle JSON data structures, enabling complex querying and manipulation of hierarchical data using functions designed for semi-structured data.
References:
* Snowflake Documentation: VARIANT Data