ISBN: 9798906960573 - data engineering in the cloud: architectures, pipelines, and best practices (8 resultados)

Condición: New.

Hardcover. Condición: new. 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. …

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Buch. Condición: Neu. Data Engineering in the Cloud | Architectures, Pipelines, and Best Practices | Rahul Abhinav Polaboina | Buch | Englisch | 2026 | Notion Press | EAN 9798906960573 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Hardcover. Condición: new. 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 our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. …

Hardcover. Condición: new. 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 our UK warehouse or from our Australian or US warehouses, depending on stock availability. …