This book is a comprehensive guide to using Python for data engineering, providing an in-depth exploration of essential concepts and practical applications. Key features
- Coverage of essential data engineering concepts - Detailed explanations of data pipeline architectures - In-depth look at ETL (Extract, Transform, Load) processes - Advanced topics such as real-time data processing, workflow orchestration, and data integration
You'll gain valuable skills in building scalable data pipelines and workflows through hands-on tutorials and practical examples. Each chapter is rich with code examples that illustrate key concepts, making the learning process engaging and effective.
Additionally, the book includes a special chapter called "Glossary," which clarifies important terms and definitions, ensuring you have a solid understanding of the terminology used throughout the text.