Advanced Data Engineering with Snowflake Part 1: DevOps with Snowflake!
Welcome to Part 1: DevOps with Snowflake! In part 1, you'll learn how DevOps helps software development teams iterate safely and efficiently, and understand how those practices can be applied in the field of data engineering.
You'll learn how to implement a few key DevOps best practices for data pipelines. Namely, you'll learn how to implement source control for pipeline objects, how to declaratively manage database objects, and how to introduce changes to dedicated data development environments using continuous integration.
By the end of the module, you'll understand how data pipelines can be built collaboratively by large teams, and how they can be evolved efficiently and reliably.
Objectives
After completing this course, you will be able to:
- •Add collaboration to data pipeline development workflows by using GitHub and pull requests.
- •Implement automated deployments, create and deploy dedicated development and production data environments, and implement source control for data pipeline objects.
- •Understand database change management (DCM), and common approaches to DCM, including imperative and declarative approaches.
- •Understand the DevOps best practices covered in the course: collaboration, source control, continuous delivery, efficiency with command-line interfaces, and which Snowflake features support DevOps.
- •Understand how DevOps best practices can be applied in the field of data engineering.
Audience
- •Technical Sales
- •Consultants
Learning Tracks
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