SQL Server 2017 Machine Learning Services with R: Data exploration, modeling, and advanced analytics

by Tomaz Kastrun, Julie Koesmarno

Overview

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.

Product Details

ISBN-13:	9781787280922
Publisher:	Packt Publishing
Publication date:	02/27/2018
Sold by:	Barnes & Noble
Format:	eBook
Pages:	338
File size:	9 MB

About the Author

Tomaz Kastrun is a SQL Server developer and data scientist with more than 15 years of experience in the fields of business warehousing, development, ETL, database administration, and query tuning. He holds over 15 years of experience in data analysis, data mining, statistical research, and machine learning. He is a Microsoft SQL Server MVP for data platform and has been working with Microsoft SQL Server since version 2000. He is a blogger, author of many articles, a frequent speaker at the community and Microsoft events. He is an avid coffee drinker who is passionate about fixed gear bikes.

Julie Koesmarno is a senior program manager in the Database Systems Business Analytics team, at Microsoft. Currently, she leads big data analytics initiatives, driving business growth and customer success for SQL Server and Azure Data businesses. She has over 10 years of experience in data management, data warehousing, and analytics for multimillion-dollar businesses as a SQL Server developer, a system analyst, and a consultant prior to joining Microsoft. She is passionate about empowering data professionals to drive impacts for customer success and business through insights.

Table of Contents

Table of Contents

1. Introduction to R and SQL Server
2. Overview of Microsoft Machine Learning Server and SQL Server
3. Managing Machine Learning Services for SQL Server 2017 and R
4. Data exploration and data visualization
5. RevoScaleR package
6. Predictive modelling
7. Operationalizing R Code
8. Deploying, managing, and monitoring database solutions Containing R Code
9. Machine learning Services with R for DBAs
10. R and SQL Server 2016/2017 extended