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)

Gathering relevant data

Gathering data - simple as it might be - is a task that needs to be well crafted. There are a few reasons for that. The first and most important is that we want to gather data in a way that will have minimum or zero impact on the production environment. This means that the process of collecting and storing data should not disturb any on-going process. The second important thing is storage. Where and how do you want to store the data and the retention policy of the stored data? At the beginning, this might seem a very trivial case, but over time, storage itself will play an important role. The third and also utterly important thing is which data you want to gather. Of course, we all want to have smart data present, that is, having all the data relevant for solving or improving our business processes. But in reality, gathering smart is neither that difficult...