Cloud Data Design,Orchestration,and Management Using Microsoft Azure

Cloud Data Design,Orchestration,and Management Using Microsoft Azure: Master and Design a Solution Leveraging the Azure Data Platform
Cloud Data Design,Orchestration,and Management Using Microsoft Azure: Master and Design a Solution Leveraging the Azure Data Platform
by 作者: Francesco Diaz - Roberto Freato
ISBN-10 书号: 1484236149
ISBN-13 书号: 9781484236147
Edition 版本: 1st ed.
Publisher Finelybook 出版日期: 2018-08-26
Pages: 438


Book Description
Cloud Data Design,Orchestration,and Management Using Microsoft Azure: Master and Design a Solution Leveraging the Azure Data Platform
Use Microsoft Azure to optimally design your data solutions and save time and money. Scenarios are presented covering analysis,design,integration,monitoring,and derivatives.
This book is about data and provides you with a wide range of possibilities to implement a data solution on Azure,from hybrid cloud to PaaS services. Migration from existing solutions is presented in detail. Alternatives and their scope are discussed. Five of six chapters explore PaaS,while one focuses on SQL Server features for cloud and relates to hybrid cloud and IaaS functionalities.
What You’ll Learn
Know the Azure services useful to implement a data solution
Match the products/services used to your specific needs
Fit relational databases efficiently into data design
Understand how to work with any type of data using Azure hybrid and public cloud features
Use non-relational alternatives to solve even complex requirements
Orchestrate data movement using Azure services
Approach analysis and manipulation according to the data life cycle

Who this book is for
Software developers and professionals with a good data design background and basic development skills who want to learn how to implement a solution using Azure data services
Cover
Frontmatter
1.Working with Azure Database Services Platform
2.Working with SQL Server on Hybrid Cloud and Azure laas
3.Working with NoSQL Alternatives
4.Orchestrate Data with Azure Data Factory
5.Azure Data Lake Store and Azure Data Lake Analytics
6.Working with In-Transit Data and Analytics

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