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Python for Data Engineering: Building Scalable Data Pipelines and Workflows
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.
- 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.
255 pages, Kindle Edition
Published June 19, 2024
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