Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
SQL Server 2017 Developer???s Guide

You're reading from   SQL Server 2017 Developer???s Guide A professional guide to designing and developing enterprise database applications

Arrow left icon
Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788476195
Length 816 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
Miloš Radivojević Miloš Radivojević
Author Profile Icon Miloš Radivojević
Miloš Radivojević
William Durkin William Durkin
Author Profile Icon William Durkin
William Durkin
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Introduction to SQL Server 2017 FREE CHAPTER 2. Review of SQL Server Features for Developers 3. SQL Server Tools 4. Transact-SQL and Database Engine Enhancements 5. JSON Support in SQL Server 6. Stretch Database 7. Temporal Tables 8. Tightening Security 9. Query Store 10. Columnstore Indexes 11. Introducing SQL Server In-Memory OLTP 12. In-Memory OLTP Improvements in SQL Server 2017 13. Supporting R in SQL Server 14. Data Exploration and Predictive Modeling with R 15. Introducing Python 16. Graph Database 17. Containers and SQL on Linux 18. Other Books You May Enjoy

Summary

For SQL Server developers, this must have been quite an exhausting chapter. Of course, the whole chapter is not about the T-SQL language; it's about the R language, and about statistics and advanced analytics. Of course, developers can also profit from the capabilities that the new language has to offer. You learned how to measure associations between discrete, continuous, and combinations of discrete and continuous variables. You learned about directed and undirected data mining and machine learning methods. Finally, you saw how to produce quite advanced graphs in R.

Please be aware that if you want to become a real data scientist, you need to learn more about statistics, data mining and machine learning algorithms, and practice programming in R. Data science is a long learning process, just like programming and development. Therefore, when you start using R, you...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime