Book Image

SQL Server 2017 Machine Learning Services with R.

By : Julie Koesmarno, Tomaž Kaštrun
Book Image

SQL Server 2017 Machine Learning Services with R.

By: Julie Koesmarno, Tomaž Kaštrun

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.
Table of Contents (12 chapters)

R and SQL Server 2016/2017 Features Extended

SQL Server 2016 and 2017 provide a lot of new and improved query performance capabilities, extensibility features, security features, and built-in/native capabilities that are useful for developers, DBAs, and data scientists. These new features and capabilities can be used together with machine learning services in SQL, bringing a powerful data science solution as well as making the life of the developer/data scientist much easier.

This chapter will walk you through a few unique scenarios to show the combined power of R and other built-in capabilities in SQL Server. These scenarios include JSON built-in capabilities to show how we work with IoT data, PolyBase to illustrate beyond relational data sources, and a large amount of data with the ColumnStore index. We will dive into these scenarios and produce data visualization and predictive...