The text discusses how modern data engineering teams face repetitive, tedious tasks due to the massive data explosion resulting from digital transformation. These teams are responsible for ensuring the reliability and optimization of data supply chains but have been overwhelmed by the COVID-19 pandemic, leading to burnout and resignations. Automation is seen as a solution to these challenges, with machine learning used to predict issues and improve accuracy in data management. Acceldata provides multidimensional data observability for platforms, data, and pipelines, automating data reliability across hybrid data lakes, warehouses, and streams. The text also presents a specific use case of Compute Observability for Snowflake, highlighting how Acceldata's automation can address various requirements for effective Snowflake management.