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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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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

Exploring dynamic data masking


With the new SQL Server 2016 and Dynamic Data Masking (DDM), you have an additional tool that helps you limit the exposure of sensitive data by masking it to non-privileged users. The masking is done on the SQL Server side, and thus you don't need to implement any changes to applications so they can start using it. DDM is available in the Standard, Enterprise, and Developer Editions; you can read the official documentation about it at:

https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking.

This section introduces DDM, including:

  • Defining masked columns
  • DDM limitations

Defining masked columns

You define DDM at the column level. You can obfuscate values from a column in a table by using four different masking functions:

  • The default function implements full masking. The mask depends on the data type of the column. A string is masked by changing each character of a string to X. Numeric values are masked to zero. Date and time data type...
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