Synopsis
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 Technology
Build 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Vlad Riscutia is a software architect and data engineer at Microsoft on the Customer Growth and Analytics team.
À propos de la quatrième de couverture
About the book.
In Data Engineering on Azure you'll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you'll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Data Engineering on Azure
Edité par
Manning, 2021
ISBN 10 : 1617298921
ISBN 13 : 9781617298929
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Data Engineering on Azure
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ISBN 10 : 1617298921
ISBN 13 : 9781617298929
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Data Engineering on Azure
Edité par
Manning (edition ), 2021
ISBN 10 : 1617298921
ISBN 13 : 9781617298929
Ancien ou d'occasion
Paperback
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Data Engineering on Azure Format: Paperback
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ISBN 10 : 1617298921
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Data Engineeringon Azure
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ISBN 10 : 1617298921
ISBN 13 : 9781617298929
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Paperback. Etat : 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. N° de réf. du vendeur LU-9781617298929
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Data Engineeringon Azure (Paperback)
Edité par
Manning Publications, New York, 2022
ISBN 10 : 1617298921
ISBN 13 : 9781617298929
Neuf
Paperback
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Paperback. Etat : 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. N° de réf. du vendeur 9781617298929
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Data Engineering on Azure
Edité par
Manning, 2021
ISBN 10 : 1617298921
ISBN 13 : 9781617298929
Ancien ou d'occasion
Couverture souple
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