15 Essential Steps To Build Reliable Data Pipelines

Description

Summary

• Every Data Pipeline Will Fail — How to Prepare For It If I learned anything from working as a data engineer, it is that practically any data pipeline fails at some point.
• Broken connection, broken dependencies, data arriving too late, or some external systems or APIs unreachable… There are many reasons why the failure may occur, but regardless of the cause, we can do a lot to mitigate the impact of a data pipeline’s failure.
• From my experience, it pays off to make data pipelines as small and dependency-free as possible.
• The worst-case scenario for a data engineering team is a monitoring system where there are so many error messages flowing into your notification channel that people stop looking at it or mute it forever.