Customers use Snowflake to build, deploy, and operate their business critical, and often complex, data-intensive workloads in the cloud. However, it’s difficult for customers to effectively monitor and optimize their Snowflake infrastructure and data quality, which leads to inefficient resource utilization, higher costs, and a degraded customer experience. For example, errors in Snowflake Marketplace or Snowpark apps may not be noticeable until they are flagged by customers, or a breaking ETL change may not be discovered until dashboards and reports are empty. To resolve errors and incidents like these, multiple teams often use several tools and perform manual troubleshooting steps, resulting in higher time to resolution.In this session, you will learn how Datadog’s Snowflake integration enables SREs, data engineers, and application developers to identify data and performance issues at a glance. We will demonstrate how to detect data quality abnormalities and their root causes, uncover long running queries to improve performance and reduce costs, identify real time security threats, and monitor your Snowpark workloads.