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Using this book

In this book, you’ll learn how to install, configure, and use Microsoft’s SQL Server R Services in data science projects. We’re assuming that you have familiarity with data science and, most important, the R language. But if you don’t, we’ve added a section here to help you get started with this powerful data-analysis environment.

For the data science or R professional

“Data science” is a relatively new term, and it has a few definitions. For this book, we’ll use the name itself to define it. Thus a data science professional is a technical professional who uses a scientific approach (asks a question, creates a hypothesis—or more accurately a model—tests the hypothesis, and then communicates the results) in the data-analytics process, whether using structured or unstructured data, or perhaps both.

We’re assuming that you have a background in general mathematics, some linear algebra, and, of course, an in-depth familiarity with statistics. We’re also assuming that you know the R language and its processing environment and are familiar with how to load various packages, and that you understand when to use R for a given data solution. But even if you don’t have those skills, read on; we have some resources that you can use. Even if you have a deep background in statistics and R, Microsoft’s SQL Server might be new to you. To learn how to work with it, take a look at the section “SQL Server and Transact-SQL” later in this chapter. In this book, we’ll assume that you have a working knowledge of how SQL Server operates, and how to read and write Transact-SQL—the dialect of the SQL language that Microsoft implements in SQL Server.

In the two chapters that follow, we’ll show you what SQL Server R Services is all about and how you can install it. You’ll learn the client tools and the way to work with R Services, and we’ll follow that up with a walk-through using the data science process. One of the best ways to learn to work with a product is to deconstruct some practical examples in which it is used. In the rest of this book, we’ve put together representative, real-world use cases that demonstrate an end-to-end solution for a typical data science project. These are examples you’ll find in other data science tools, so you should be able to extrapolate the concepts of what you already know to how you can do the same thing in SQL Server using R Services—we think you’ll find it has some real advantages to using a standard R platform.