1. Secrets of production-level data pipelines in Python – Building and managing automated data workflows with Luigi and Airflow – (Japanese Edition)
Written by Rin Sakakuni, this book is a treasure trove for data engineers looking to enhance their knowledge on automating data workflows. The author dives deep into the workings of Luigi and Airflow, two powerful tools in the realm of data pipeline construction. This book demystifies the complexities of production-level data pipelines, making it accessible for beginners while still offering valuable insights for seasoned professionals.
One of the highlights of this book is its practical approach, filled with real-world examples that bring the concepts to life. Readers will appreciate the step-by-step instructions that guide them through the process of setting up and managing automated workflows effectively. Whether you’re working with large datasets or simply looking to optimize your processes, this book lays down a clear framework for success.
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2. Python for Data Engineering: Build ETL Pipelines and Handle Big Data Efficiently with Python
Authored by Greyson Chesterfield, this book is an essential guide for anyone looking to delve into data engineering using Python. It covers the necessary skills for building robust ETL (Extract, Transform, Load) pipelines, emphasizing efficiency and scalability in handling big data. The writing is clear, and the book is structured methodically, making it an easy read for those new to the field.
The author leverages practical examples alongside comprehensive explanations, ensuring that readers not only understand the theory but also how to apply these concepts in practical scenarios. With data being one of the most valuable assets today, mastering the skills outlined in this book can significantly boost your career in data engineering.
Explore this indispensable resource and start your journey toward mastering data pipes! Find it here.
