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The Data Engineering Lifecycle Print

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How work proceeds.

WHAT THE STAGES ARE

Understanding the requirement Identifying and assessing sources Designing the model Building ingestion Building transformation Testing Deploying and scheduling Monitoring Maintaining

WHAT TO ESTABLISH FIRST

What question the data must answer, and who will act on it.

WHY

It determines what to collect, how fresh it must be, and how accurate.

WHAT TO AVOID

Building a pipeline before knowing what it serves.

WHAT TO DELIVER FIRST

A thin path end to end: one source, minimal transformation, one useful output.

WHY

It proves the approach and surfaces problems early.

WHAT MAINTENANCE ACTUALLY INVOLVES

Sources changing Volumes growing Requirements changing Failures needing investigation

WHAT PROPORTION OF EFFORT THAT IS

The majority, over a pipeline's life.

WHAT THAT MEANS FOR DESIGN

Build for the person maintaining it, including future you.

WHAT TO DOCUMENT

Where data comes from, what was done to it, and why.


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