Data Science with Microsoft SQL Server 2016
Book Details
| Authors | Buck Woody, Danielle Dean, Debraj GuhaThakurta, Gagan Bansal, Matt Conners, Wee-Hyong Tok |
| Publisher | Microsoft Press |
| Published | 2016 |
| Edition | 1 |
| Paperback | 90 pages |
| Language | English |
| ISBN-13 | 9781509304318 |
| ISBN-10 | 1509304312 |
| License | Open Access |
Book Description
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.
This book breaks down into three primary sections: an introduction to the SQL Server R Services and SQL Server in general, a description and explanation of how a data scientist works in this new environment (useful, given that many data scientists work in "silos," and this new way of working brings them in to the business development process), and practical, hands-on examples of working through real-world solutions. The reader can either review the examples, or work through them with the chapters.
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.
This book is published as open-access, which means it is freely available to read, download, and share without restrictions.
If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.
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