Finding Expensive Queries in Snowflake by Calculating Cost per Query

The article explores strategies for identifying and managing expensive queries in Snowflake, a cloud-based data warehouse with a usage-based pricing model. It highlights methods to calculate the cost per query by examining factors such as query execution time and warehouse size, using SQL queries that pull data from Snowflake's QUERY_HISTORY and WAREHOUSE_SIZE tables. The piece also discusses the application of query tags, which allow businesses to track costs associated with specific units, such as teams or services, thus optimizing resource usage. By leveraging these techniques, organizations can align data consumption with business processes and improve cost efficiency. The article underscores the importance of these practices as part of data engineering efficiency, offering tools and methods for better financial management and encouraging readers to sign up for a Vantage demo to further explore these capabilities.