Book Image

Professional Azure SQL Managed Database Administration - Third Edition

By : Ahmad Osama, Shashikant Shakya
Book Image

Professional Azure SQL Managed Database Administration - Third Edition

By: Ahmad Osama, Shashikant Shakya

Overview of this book

Despite being the cloud version of SQL Server, Azure SQL Database and Azure SQL Managed Instance stands out in various aspects when it comes to management, maintenance, and administration. Updated with the latest Azure features, Professional Azure SQL Managed Database Administration continues to be a comprehensive guide for becoming proficient in data management. The book begins by introducing you to the Azure SQL managed databases (Azure SQL Database and Azure SQL Managed Instance), explaining their architecture, and how they differ from an on-premises SQL server. You will then learn how to perform common tasks, such as migrating, backing up, and restoring a SQL Server database to an Azure database. As you progress, you will study how you can save costs and manage and scale multiple SQL databases using elastic pools. You will also implement a disaster recovery solution using standard and active geo-replication. Finally, you will explore the monitoring and tuning of databases, the key features of databases, and the phenomenon of app modernization. By the end of this book, you will have mastered the key aspects of an Azure SQL database and Azure SQL managed instance, including migration, backup restorations, performance optimization, high availability, and disaster recovery.
Table of Contents (14 chapters)
13
Index

Machine Learning Services

Machine Learning Services was first introduced in SQL Server 2016 (on-premises) as R Services. Machine learning is now available in Azure SQL Managed Instance. It's in preview at the time of writing.

Machine Learning Services provides machine learning capabilities for Azure SQL Managed Instance and allows in-database R and Python scripts to be run for high-performance predictive analytics. Running in-database R and Python scripts uses the data in the managed instance instead of pulling the data over the network from a different source. In the absence of Machine Learning Services, you would have to set up R and Python and get the data from a remote data source for the analysis.

Machine Learning Services makes it possible to run R and Python scripts in stored procedures or T-SQL statements.

R is a programming language that's extensively used for data analysis, machine learning, and predictive analytics. R packages provide out-of-the-box methods...