Snowflake is a self-managed data platform that enables users to easily store, process, analyze, and share high volumes of structured and semi-structured data. It has gained widespread adoption due to its unified, scalable, and high-performance platform, flexibility, and built-in dashboards and integration with business intelligence (BI) tools like Tableau and Power BI. Data scientists use Snowflake's integrations with tools like Python and TensorFlow to train machine learning (ML) models, while media platforms can use real-time analytics from Snowflake to track user engagement and optimize content delivery. However, monitoring Snowflake is important for teams due to its complexity and the potential for high costs, particularly if they are using it for multiple purposes or processing large datasets. To monitor Snowflake, teams should focus on tracking metrics such as warehouse query performance, storage usage, and task history to ensure optimal performance, cost optimization, and data accuracy.