Advanced Data Engineering with Snowflake
Advanced Data Engineering with Snowflake
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 3m | 379 MB
Created by Snowflake, Inc
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 3m | 379 MB
Created by Snowflake, Inc
This is a technical, hands-on course that teaches you how to implement DevOps best practices to build data pipelines, and how to implement observability to maintain and monitor data pipeline health. Discover the most practical Snowflake concepts, features, and tools to help you get you up and running quickly on the platform. Get started by learning about DevOps, DevOps practices, and how DevOps fits into the context of data engineering. Find out how to incorporate source control, declarative management of database objects, continuous delivery, and use the command-line interface to implement DevOps best practices into a data pipeline. Throughout the course, you’ll follow along with the instructor using a combination of Snowflake, VS Code, GitHub, and the command line.
Learning objectives
- Implement DevOps best practices for data pipelines with Snowflake.
- Leverage Snowflake's Git integration to add source control to your data pipeline.
- Use GitHub for team-wide collaboration on your data pipeline.
- Apply CREATE OR ALTER to declaratively manage database objects.
- Implement continuous delivery for your pipeline using GitHub Actions.
- Deploy changes into dedicated data environments from the Snowflake command-line interface.
- Implement observability to maintain and monitor the health and performance of your data pipeline.
- Keep detailed records of events that occur within your pipeline using logs and traces.
- Utilize alerts to monitor for specific conditions in your pipeline, and combine them with notifications to encourage action among team members if critical errors occur in the pipeline.
Advanced Data Engineering with Snowflake
