R is one of the most popular, powerful data analytics languages and environments in use by data scientists. Actionable business data is often stored in Relational Database Management Systems (RDBMS), and one of the most widely used RDBMS is Microsoft SQL Server. Much more than a database server, it's a rich ecostructure with advanced analytic capabilities. Microsoft SQL Server R Services combines these environments, allowing direct interaction between the data on the RDBMS and the R language, all while preserving the security and safety the RDBMS contains. In this book, you'll learn how Microsoft has combined these two environments, how a data scientist can use this new capability, and practical, hands-on examples of using SQL Server R Services to create real-world solutions.
The intended audience for this book is technical - specifically, the data scientist - and is assumed to be familiar with the R language and environment. We do, however, introduce data science and the R language briefly, with many resources for the reader to go learn those disciplines, as well, which puts this book within the reach of database administrators, developers, and other data professionals. Although we do not cover the totality of SQL Server in this book, references are provided and some concepts are explained in case you are not familiar with SQL Server, as is often the case with data scientists.
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- Title: Data Science with Microsoft SQL Server 2016
- Authors: Buck Woody, Danielle Dean, Debraj GuhaThakurta, Gagan Bansal, Matt Conners, Wee-Hyong Tok
- Publisher: Microsoft Press
- ISBN: 9781509304318, 1509304312
- Paperback: 90 pages
- Publication date: 2016
- License: Open Access