The Query Profile in Snowflake can identify common query problems, including:
* B. Inefficient pruning: This refers to the inability of a query to effectively limit the amount of data being scanned, potentially leading to suboptimal performance.
* D. Queries too large to fit in memory: This indicates that a query requires more memory than is available in the virtual warehouse, which can lead to spilling to disk and degraded performance.
The Query Profile helps diagnose these issues by providing detailed execution statistics and visualizations, aiding in query optimization and troubleshooting.
References:
* Snowflake Documentation: Query Profile
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The FLATTEN function can be used with the recursive argument to return a list of distinct key names in all nested elements within an object. This function is particularly useful for working with semi-structured data in Snowflake

To generate a report listing all Snowflake logins within the last 90 days, the ACCOUNT_USAGE.
LOGIN_HISTORY view should be used. This view provides information about login attempts, including successful and unsuccessful logins, and is suitable for security audits4.