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Key benefits

Understand how to set up a Python virtual environment with PyCharm

Learn functional and object-oriented approaches to create ETL pipelines

Create robust CI/CD processes for ETL pipelines

Purchase of the print or Kindle book includes a free PDF eBook

Description

Modern extract, transform, and load (ETL) pipelines for data engineering have favored the Python language for its broad range of uses and a large assortment of tools, applications, and open source components. With its simplicity and extensive library support, Python has emerged as the undisputed choice for data processing. In this book, you’ll walk through the end-to-end process of ETL data pipeline development, starting with an introduction to the fundamentals of data pipelines and establishing a Python development environment to create pipelines. Once you've explored the ETL pipeline design principles and ET development process, you'll be equipped to design custom ETL pipelines. Next, you'll get to grips with the steps in the ETL process, which involves extracting valuable data; performing transformations, through cleaning, manipulation, and ensuring data integrity; and ultimately loading the processed data into storage systems. You’ll also review several ETL modules in Python, comparing their pros and cons when building data pipelines and leveraging cloud tools, such as AWS, to create scalable data pipelines. Lastly, you’ll learn about the concept of test-driven development for ETL pipelines to ensure safe deployments. By the end of this book, you’ll have worked on several hands-on examples to create high-performance ETL pipelines to develop robust, scalable, and resilient environments using Python.

What you will learn

Explore the available libraries and tools to create ETL pipelines using Python

Write clean and resilient ETL code in Python that can be extended and easily scaled

Understand the best practices and design principles for creating ETL pipelines

Orchestrate the ETL process and scale the ETL pipeline effectively

Discover tools and services available in AWS for ETL pipelines

Understand different testing strategies and implement them with the ETL process

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Packt verified reviews

Amazon verified reviews

Data Science Leader Oct 18, 2023

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!

Amazon Verified review

Amir Esmaeili Nov 15, 2023

Einfach Super!

H2N Oct 18, 2023

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.

Deblina Dec 02, 2023

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.

Om S Oct 17, 2023

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.

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

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