DataGrip使用技巧总结

datagrip激活 • 2024-10-25 20:30 • 阅读 21

大家好，我是考100分的小小码，祝大家学习进步，加薪顺利呀。今天说一说DataGrip使用技巧总结,希望您对编程的造诣更进一步.

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.