After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
코스 설명
Take your Snowflake data pipelines to production with DevOps and observability. In this hands-on course, you'll implement source control with Git, manage database changes declaratively using CREATE OR ALTER, and automate deployments with the Snowflake CLI and GitHub Actions. Then you'll make pipelines observable with Snowflake Trail, using event tables, logging, traces, alerts, and notifications to monitor pipeline health and respond quickly when issues arise. By the end, you'll be able to build, deploy, and maintain reliable pipelines that scale with modern demands.
사전 요구 사항
커리큘럼
코스 개요
1
DevOps with Snowflake
Learn how to apply DevOps best practices to Snowflake data pipelines, from source control with Git to declarative database changes with CREATE OR ALTER and automated CI/CD using the Snowflake CLI and GitHub Actions.
- Scaling data pipelines to meet modern demands50 XP
- What this course will cover50 XP
- DevOps in the world of data engineering50 XP
- DevOps with Snowflake50 XP
- What we'll build50 XP
- Source control in Snowflake with git50 XP
- Clone your fork, install Snowflake CLI, and configure config.toml50 XP
- Weather data from Snowflake Marketplace50 XP
- Set up the data pipeline using Snowflake CLI50 XP
- Database Change Management (DCM)50 XP
- Declarative approach with CREATE OR ALTER50 XP
- Continuous integration and continuous delivery (CI/CD) for data pipelines50 XP
- Implementing continuous delivery for our data pipeline50 XP
- Recap and best practices for DevOps with Snowflake50 XP
- Additional resources on DevOps with Snowflake50 XP
- Chapter 1 review - Question 150 XP
- Chapter 1 review - Question 250 XP
- Chapter 1 review - Question 350 XP
- Chapter 1 review - Question 450 XP
- Chapter 1 review - Question 550 XP
2
Observability with Snowflake
In this final chapter, you'll learn how to make data pipelines observable with Snowflake Trail, using event tables, logging, traces, alerts, and notifications to monitor pipeline health and act on issues quickly.
R
Advanced Data Engineering with Snowflake
코스
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