The command USE WAREHOUSE <<warehouse name>>; is used to set the virtual warehouse for the current session in Snowflake. This command specifies which virtual warehouse to use for executing queries in that session1.

To change a Standard virtual warehouse to a Snowpark-optimized virtual warehouse, the warehouse must be in a suspended state. This ensures that no operations are disrupted during the modification process.
Suspend the Warehouse: Ensure that the warehouse is suspended.
ALTER WAREHOUSE my_warehouse SUSPEND;
Alter the Warehouse: Modify the warehouse to be Snowpark-optimized.
ALTER WAREHOUSE my_warehouse SET WAREHOUSE_TYPE = 'SNOWPARK-OPTIMIZED'; Resume the Warehouse: Resume the warehouse to make it operational.
ALTER WAREHOUSE my_warehouse RESUME;
Reference:
Snowflake Documentation: Creating Snowpark-Optimized Warehouses
Snowflake Documentation: ALTER WAREHOUSE

To monitor updates, such as SCIM API requests sent to Snowflake by the identity provider, an administrator can use the REST EVENT HISTORY feature. This feature allows administrators to query historical data about REST API calls made to Snowflake, including those related to user and role management through SCIM (System for Cross-domain Identity Management).
The REST EVENT HISTORY table function returns information about REST API calls made over a specified period. It is particularly useful for auditing and monitoring purposes, especially when integrating Snowflake with third-party identity providers that use SCIM for automated user provisioning and deprovisioning.
An example query to check for SCIM API requests might look like this:
SELECT * FROM TABLE(information_schema.rest_event_history(date_range_start=>dateadd('hours',-1,current_timestamp()))) WHERE request_type = 'SCIM'; This query returns details on SCIM API requests made in the last hour, including the request type, the identity provider's details, and the outcome of each request.

The statistics that can be used to identify queries with inefficient pruning are 'Partitions scanned' and 'Partitions total'. These statistics indicate how much of the data was actually needed and scanned versus the total available, which can highlight inefficiencies in data pruning34.

To manage compliance with Personal Identifiable Information (PII) requirements, the Virtual Private Snowflake and Business Critical Editions of Snowflake should be used. These editions provide advanced security features necessary for handling sensitive data