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)

Overcomming R language limitations

Prior to SQL Server 2016 (and 2017) BI and data scientists had the OLAP cubes, DMX language, and all super awesome and cool Microsoft algorithms available within SQL Server Analysis Services (SSAS). But, with rapid changes and bigger market demands, the need for integration of an open-source product (whether R, Python, Perl,or any other) was practically already there. And the next logical step was to integrate it with one. Microsoft sought a solution and ended up acquiring Revolution Analytics, which has put them on track again. Revolution R has addressed major issues concerning the R language.

Microsoft addressed R's limitations. Many of these limitations were aimed at faster data exploration and parallel programming techniques in R. In addition to this, also MKL computations have been enhanced, therefore making matrix-wise calculations...