Orchestrate and Automate Data Workflows in Snowflake

Automating data workflows in Snowflake is key to scalable data operations. This course will teach you how to build resilient, efficient pipelines using Tasks, Streams, and task chaining for orchestration and monitoring.

Orchestrating and automating data workflows is critical to ensuring timely, reliable, and efficient data operations in modern platforms. Yet many data professionals struggle to build robust pipelines that are both scalable and easy to monitor. In this course, Orchestrate and Automate Data Workflows in Snowflake, you’ll gain the ability to build resilient, automated pipelines using native Snowflake features. First, you’ll explore how to use Snowflake Tasks to schedule and run recurring SQL operations, monitor execution, and embed procedural logic with Snowflake Scripting. Next, you’ll discover how to use Streams to implement change data capture for incremental data pipelines, efficiently tracking inserts, updates, and deletes. Finally, you’ll learn how to build multi-step workflows using task dependencies, implement recovery and monitoring mechanisms, and integrate Snowflake Tasks with external orchestration tools like Airflow and dbt. When you’re finished with this course, you’ll have the skills and knowledge of workflow orchestration and automation in Snowflake needed to confidently build scalable, maintainable data pipelines.