Snowflake retains information in the ACCESS HISTORY view for 365 days. This allows users to query the access history of Snowflake objects within the last year1.

Automatic Clustering is a feature that allows users to control the organization of data within micro-partitions in Snowflake. By defining clustering keys, Snowflake can automatically reorganize the data in micro-partitions to optimize query performance1.

* Snowsight is Snowflake's web-based interface used for managing and monitoring data, query performance, and user activities.
* It provides detailed analytics and dashboards to track usage, monitor query execution, and review account activity for governance and optimization.
* Example: Administrators use Snowsight to track user sessions, queries, and compute resource utilization.
References:
* Snowflake Documentation: Snowsight Overview
* Snowsight Usage Monitoring

In Snowflake, stored procedures and User-Defined Functions (UDFs) have different invocation patterns within SQL:
Option B is correct: A single executable statement can call only one stored procedure due to the procedural and potentially transactional nature of stored procedures. In contrast, a single SQL statement can call multiple UDFs because UDFs are designed to operate more like functions in traditional programming, where they return a value and can be embedded within SQL queries.
Reference: Snowflake documentation comparing the operational differences between stored procedures and UDFs.