ETL Pipelines

The data you need is rarely in one clean place. It is spread across production databases, APIs, files, and event streams. Each source has its own format, timing, and edge cases. Moving that data into a place where people can trust and query it is real engineering work.

That is what an ETL pipeline does. It extracts data from source systems, transforms it into a usable shape, and loads it into a destination for analytics, applications, or machine learning.

A production pipeline is more than a copy job. It protects source systems, handles retries safely, validates data, records where data came from, and supports backfills so users get reliable data.

This chapter covers how extract, transform, and load work, how ETL differs from ELT, how to design reliable pipelines, and how to handle failures and backfills.