Data Engineering in the Cloud (Hardcover)
Published by Notion Press, 2026
- Hardcover
- New

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
US$ 33.52
Quantity: 1 available
Add to basketItem description from seller
Hardcover. Data Engineering in the Cloud: Architectures, Pipelines, and Best Practices is a comprehensive guide to designing, building, and managing modern cloud-based data platforms. Covering the complete data engineering lifecycle, the book explores cloud infrastructure, scalable architectures, distributed processing, data lakes, data warehouses, and lakehouses. Readers will learn how to develop reliable data pipelines, automate workflows, ensure data quality, and optimize performance for large-scale analytical workloads. The book also addresses critical topics such as security, governance, compliance, disaster recovery, and cost optimization, while introducing DataOps, DevOps, MLOps, and Infrastructure as Code (IaC) for efficient data platform management. Looking ahead, it examines AI-driven automation, Generative AI applications, and emerging technologies shaping the future of cloud data engineering. Combining foundational concepts with practical best practices, this book serves as an essential resource for students, researchers, cloud architects, data engineers, and IT professionals seeking to build scalable, secure, and high-performance cloud data solutions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9798906960573
- Title
- Data Engineering in the Cloud (Hardcover)
- Author
- Rahul Abhinav Polaboina
- Publisher
- Notion Press
- Publication year
- 2026
- Condition
- new
- Binding
- Hardcover
- ISBN 13
- 9798906960573
Data Engineering in the Cloud: Architectures, Pipelines, and Best Practices is a comprehensive guide to designing, building, and managing modern cloud-based data platforms. Covering the complete data engineering lifecycle, the book explores cloud infrastructure, scalable architectures, distributed processing, data lakes, data warehouses, and lakehouses. Readers will learn how to develop reliable data pipelines, automate workflows, ensure data quality, and optimize performance for large-scale analytical workloads. The book also addresses critical topics such as security, governance, compliance, disaster recovery, and cost optimization, while introducing DataOps, DevOps, MLOps, and Infrastructure as Code (IaC) for efficient data platform management. Looking ahead, it examines AI-driven automation, Generative AI applications, and emerging technologies shaping the future of cloud data engineering. Combining foundational concepts with practical best practices, this book serves as an essential resource for students, researchers, cloud architects, data engineers, and IT professionals seeking to build scalable, secure, and high-performance cloud data solutions.
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Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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