Technical Guide

Understanding ETL by O’Reilly

Data pipelines for modern data architectures
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Learn how to approach implementing ETL pipelines

Extract, transform, load (ETL) is a foundational process in data engineering that underpins every data, analytics and AI workload. With the evolution of data warehouses and data lakes and the emergence of data lakehouses, a new understanding of ETL is required from data engineers. Practitioners who aim to successfully build ETL pipelines in this new world will encounter challenges such as handling real-time data ingestion, ensuring data quality, pipeline orchestration and observability. This technical guide from O’Reilly will help you gain a better understanding of modern ETL.

Read the technical guide to learn about:

  • The basics of ETL
  • The different aspects of ETL including data ingestion, transformation and orchestration
  • Best practices for dealing with pipeline issues, improving efficiency and scalability