SQL Server is no longer just a database, but has grown into a database platform - an ecosystem - which consists of many additional services (such as SSRS, SSAS, and SSIS) that supports and also extends the capabilities of modern database usage. When installing Machine Learning R Services (in a database), one should think about the ecosystem environment and which additional services would be used along with R Services. If the business need requires advanced R (or Python) integration and analytics, the Enterprise edition is the right one. If only basic R integration is needed, the standard version will cover the needs. Also, think along the lines of other analytical tools if you need analysis services or reporting services, and which developments tools would also be needed for that (for example, MDX on top of OLAP cubes and running R code against the same data...
SQL Server 2017 Machine Learning Services with R
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SQL Server 2017 Machine Learning Services with R
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Overview of this book
R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment.
This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services.
Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power.
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Current Title:
SQL Server 2017 Machine Learning Services with R
Table of Contents (12 chapters)
Preface
Free Chapter
Introduction to R and SQL Server
Overview of Microsoft Machine Learning Server and SQL Server
Managing Machine Learning Services for SQL Server 2017 and R
Data Exploration and Data Visualization
RevoScaleR Package
Predictive Modeling
Operationalizing R Code
Deploying, Managing, and Monitoring Database Solutions containing R Code
Machine Learning Services with R for DBAs
R and SQL Server 2016/2017 Features Extended
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