Building ETL Pipelines with Python: Create and deploy enterprise-ready ETL pipelines by employing modern methods

Whether you're a data scientist, data engineer, or machine learning engineer, this book is a goldmine. It breaks down the world of ETL in a way that's easy to get. Brij Kishore Pandey and Emily Schoof make it simple:They explain the difference between ETL and ELT.They share ETL design patterns.They give tips for every ETL step.I loved how they focus on doing things. They show you how to set up an ETL pipeline with Python and also with AWS tools like S3, Lambda, and Step Functions. Plus, they cover how to test your pipelines and keep everything running smooth.With so many companies using cloud tools, the bits about AWS in this book are a big win. You'll feel way more confident using these tools at work.All in all, this book is top-notch for anyone in the data world looking to step up their game. Don't miss out!

If you are looking for a book on how to build enterprise-ready ETL pipelines with python, you should check out this book.This book is a comprehensive guide that covers everything from data extraction, transformation, loading, testing, and deployment. You will learn how to use popular python libraries such as pandas, sqlalchemy, airflow, and luigi to create scalable and reliable data pipelines. You will also get practical tips and best practices on how to design, document, and monitor your pipelines.The book is full of examples and exercises that will help you apply the concepts to real-world scenarios. Whether you are a beginner or an expert in ETL, this book will help you take your skills to the next level.

This book guides you through the process of creating data pipelines using Python for real-world applications. You'll learn how to set up a Python environment, use both functional and object-oriented approaches, and build robust CI/CD processes.The book covers the fundamentals of ETL pipelines, from data extraction and cleansing to loading data. It also delves into various Python libraries and tools, including AWS services, for creating efficient pipelines. You'll discover testing strategies and best practices to ensure reliability.If you're a data engineer or software professional with basic Python knowledge, this book is for you. It provides practical insights and hands-on examples to develop high-performance ETL pipelines in Python.

An insightful read for data scientists, engineers, and data enthusiasts. This book provides a comprehensive overview of ETL data pipelines in Python, distinguishing between ETL and ELT. It delves deep into the design principles essential for scalable and robust pipelines and offers strategies for data sourcing and extraction. The hands-on tutorials present an end-to-end ETL pipeline, both in Python and AWS, shedding light on the associated AWS tools. What sets it apart is its discussion on the limitations of ETL pipelines and effective scaling techniques to meet growing demands. A must-read for those eager to enhance their data pipeline knowledge.

Definitions given about like aws glue and other tools not a practical examples given

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