Data Engineeringon Azure by Riscutia Vlad (8 results)

Paperback. Condition: New. There's a big gap between running machine learning and data processes as prototypes, and deploying them to a production cloud environment. Data Engineering on Azure reveals the architectural, operational, and data management techniques that power cloud-based data infrastructure built on the Microsoft Azure platform. Data Engineering on Azure teaches you to build a scalable and robust data platform to industry-leading standards. All examples are based on the production big data platform that powers Microsoft's customer growth operations. You'll learn techniques and best practices that author Vlad Riscutia and his team use on a daily basis, including automation and DevOps, running a reliable machine learning pipeline, and managing your data inventory. Examples are illustrated with Azure. The patterns and techniques are transferable to other cloud platforms. About the TechnologyBuild secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify.

Paperback. Condition: new. Paperback. There's a big gap between running machine learning and data processes as prototypes, and deploying them to a production cloud environment. Data Engineering on Azure reveals the architectural, operational, and data management techniques that power cloud-based data infrastructure built on the Microsoft Azure platform. Data Engineering on Azure teaches you to build a scalable and robust data platform to industry-leading standards. All examples are based on the production big data platform that powers Microsoft's customer growth operations. You'll learn techniques and best practices that author Vlad Riscutia and his team use on a daily basis, including automation and DevOps, running a reliable machine learning pipeline, and managing your data inventory. Examples are illustrated with Azure. The patterns and techniques are transferable to other cloud platforms. About the TechnologyBuild secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.

Condition: New. 2022. 1st Edition. Paperback. . . . . .

Condition: New. 2022. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condition: New. There's a big gap between running machine learning and data processes as prototypes, and deploying them to a production cloud environment. Data Engineering on Azure reveals the architectural, operational, and data management techniques that power cloud-based data infrastructure built on the Microsoft Azure platform. Data Engineering on Azure teaches you to build a scalable and robust data platform to industry-leading standards. All examples are based on the production big data platform that powers Microsoft's customer growth operations. You'll learn techniques and best practices that author Vlad Riscutia and his team use on a daily basis, including automation and DevOps, running a reliable machine learning pipeline, and managing your data inventory. Examples are illustrated with Azure. The patterns and techniques are transferable to other cloud platforms. About the TechnologyBuild secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify.

Paperback. Condition: new. Paperback. There's a big gap between running machine learning and data processes as prototypes, and deploying them to a production cloud environment. Data Engineering on Azure reveals the architectural, operational, and data management techniques that power cloud-based data infrastructure built on the Microsoft Azure platform. Data Engineering on Azure teaches you to build a scalable and robust data platform to industry-leading standards. All examples are based on the production big data platform that powers Microsoft's customer growth operations. You'll learn techniques and best practices that author Vlad Riscutia and his team use on a daily basis, including automation and DevOps, running a reliable machine learning pipeline, and managing your data inventory. Examples are illustrated with Azure. The patterns and techniques are transferable to other cloud platforms. About the TechnologyBuild secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.