When data is loaded into Snowflake, it undergoes a reorganization process where the data is stored in a columnar format and compressed. The columnar storage format enables efficient querying and data retrieval, as it allows for reading only the necessary columns for a query, thereby reducing IO operations. Additionally, Snowflake uses advanced compression techniques to minimize storage costs and improve performance. This combination of columnar storage and compression is key to Snowflake's data warehousing capabilities.
References:
* Snowflake Documentation: Data Storage and Organization

Snowflake bills virtual warehouse usage in one-minute increments, rounding up to the nearest minute for any partial minute of compute time used. If a virtual warehouse runs for 61 seconds and then, after being shut down, restarts and runs for an additional 30 seconds, the total time billed would be 120 seconds or 2 minutes.
The first 61 seconds are rounded up to 2 minutes, and the subsequent 30 seconds are within a new minute, which is also rounded up to the nearest minute.
References:
* Snowflake Documentation: Virtual Warehouses Billing

The Snowflake object that helps evaluate virtual warehouse performance impacted by query queuing is the Information_schema.warehouse_load_history. This view provides historical data about the load on a warehouse, including the average number of queries that were running or queued within a specific interval, which can be used to assess performance and identify potential issues with query queuing3.