DataGrip使用技巧总结
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.
How this book is organized
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.
Who this book is for
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.
