eBook: Microsoft Azure Data Solutions - An Introduction (DRM EPUB)
 
電子書格式: DRM EPUB
作者: Daniel A. Seara, Francesco Milano, Danilo Dominici 
系列: IT Best Practices - Microsoft Press
分類: Servers ,
Windows & variants ,
Databases ,
Cloud computing  
書城編號: 25225033


售價: $351.00

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製造商: Pearson Education
出版日期: 2021/07/14
ISBN: 9780137252527
 
>> 相關實體書

商品簡介
Discover and apply the Azure platform's most powerful data solutions   Cloud technologies are advancing at an accelerating pace, supplanting traditional relational and data warehouse storage solutions with novel, high-value alternatives. Now, three pioneering Azure Data consultants offer an expert introduction to the relational, non-relational, and data warehouse solutions offered by the Azure platform. Drawing on their extensive experience helping organizations get more value from the Microsoft Data Platform, the authors guide you through decision-making, implementation, operations, security, and more. Throughout, step-by-step tutorials and hands-on exercises prepare you to succeed, even if you have no cloud data experience.   Three leading experts in Microsoft Azure Data Solutions show how to: Master essential concepts of data storage and processing in cloud environments Handle the changing responsibilities of data engineers moving to the cloud Get started with Azure data storage accounts and other data facilities Walk through implementing relational and non-relational data stores in Azure Secure data using the least-permissions principle, Azure Active Directory, role-based access control, and other methods Develop efficient Azure batch processing and streaming solutions Monitor Azure SQL databases, blob storage, data lakes, Azure Synapse Analytics, and Cosmos DB Optimize Azure data solutions by solving problems with storage, management, and service interactions About This Book For data engineers, systems engineers, IT managers, developers, database administrators, cloud architects, and other IT professionals Requires little or no knowledge about Azure tools and services for data analysis
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