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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

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788476195
Length 816 pages
Edition 1st Edition
Languages
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Authors (3):
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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
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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 should have your code double-checked by a senior data scientist for all the tricks and tips that I haven't covered in...

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