From the course: Advanced Data Engineering with Snowflake
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Conclusion - Snowflake Tutorial
From the course: Advanced Data Engineering with Snowflake
Conclusion
I mentioned this in Introduction to Modern Data Engineering with Snowflake and it's too important not to mention again. Much of your experience is going to come from putting your hands on the keyboard and tinkering with pipelines using the documentation, videos, tutorials, and more. This goes for both concepts covered in this course, DevOps and observability. For DevOps, we covered cutting-edge features within Snowflake that allow teams to build declarative data pipelines that are able to respond quickly to constantly changing demands. You specifically learned how to use CREATE OR ALTER, Snowflake's Git integration, GitHub Actions, and Snowflake CLI to build a pipeline that can do this. For observability, we covered Snowflake Trail and you learned about the vast trove of information that you can capture and analyze about your data pipelines. This includes using event tables to capture logs and traces and using alerts and notifications to prompt action on your team. Both of these…
Contents
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Observability for data engineering3m 57s
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(Locked)
Foundational concepts of observability3m 16s
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(Locked)
Observability with Snowflake Trail2m 2s
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(Locked)
Event Tables in Snowflake4m 20s
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(Locked)
Logging in Snowflake8m 35s
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(Locked)
Traces in Snowflake8m 29s
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(Locked)
Alerts in Snowflake8m 8s
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(Locked)
Notifications in Snowflake7m 51s
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(Locked)
Observability with third-party tools59s
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(Locked)
Recap and best practices for observability with Snowflake2m 2s
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(Locked)
Conclusion1m 27s
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