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Discover the inner workings of data pipelines with 'Data Engineering with Python', a practical guide to mastering the art of data engineering. Through hands-on examples, you'll explore the process of designing data models, implementing data pipelines, and automating data flows, all within the context of Python. What this Book will help me do Understand the fundamentals of designing data architectures and capturing data requirements. Extract, clean, and transform data from various sources, refining it for precise applications. Implement end-to-end data pipelines, including staging, validation, and production deployment. Leverage Python to connect with databases, perform data manipulations, and build analytics workflows. Monitor and log data pipelines to ensure smooth, real-time operations and high quality. Author(s) Paul Crickard is a seasoned expert in data engineering and analytics, bringing years of practical experience to this technical guide. His unique ability to make complex technical concepts accessible makes this book invaluable for learners and professionals alike. A lifelong technologist, Paul focuses on actionable skills and building confidence to work with data pipelines and models. Who is it for? This book is ideal for aspiring data engineers, data analysts aiming to elevate their technical skillsets, or IT professionals transitioning into data-driven roles. Whether you're just stepping into the field or enhance your Python-based data capabilities, this book is tailored to provide solid grounding and practical expertise. Beginners in data engineering will find it accessible and easy to get started, while those refreshing their knowledge will benefit from its focused projects.