There are hundreds of different ways in which Snowflake queries and resources can be configured or optimized to improve cost efficiency. At SELECT, we’re constantly working to surface new ways to improve cost efficiency. As part of that, we’ve released the following new Insights:

• High remote disk spillage: This insight checks for workloads with excessive data spillage to remote storage. Spilling data to remote storage can significantly increase query costs.
• High backup storage: This insight checks for tables with high fail safe and time travel costs. Failsafe costs can be eliminated by converting the table to transient, whereas timetravel costs can be removed by updating the date retention policy.
• Reduce minimum cluster count: This insight checks each warehouse to see if the min_cluster_count parameter is set to a value greater than 1.
• Auto suspend disabled: This insight checks for warehouses with Auto Suspend disabled. Auto-Suspend helps minimize idle time by ensuring the warehouse is turned off when there are no more queries to run. Idle time results in wasted spend.
• High cloud services usage: This insight checks for workloads with high cloud services costs. Those are costs associated with authentication, query compilation, metadata management, and access control. Workloads can incur significant cloud services costs if they are running at a high frequency or have high compilation times due to query complexity.
• Exploding joins: This insight checks for workloads with exploding joins, which can result in higher costs due to increase data processing volumes. Exploding joins can occur when the join keys are not specified correctly, resulting in a cartesian product of the tables being joined. This can lead to higher costs and slower query performance as significantly higher volumes of data must be processed.