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Hands-On Data Science with SQL Server 2017

You're reading from   Hands-On Data Science with SQL Server 2017 Perform end-to-end data analysis to gain efficient data insight

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788996341
Length 506 pages
Edition 1st Edition
Languages
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Authors (2):
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Vladimír Mužný Vladimír Mužný
Author Profile Icon Vladimír Mužný
Vladimír Mužný
Marek Chmel Marek Chmel
Author Profile Icon Marek Chmel
Marek Chmel
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Toc

Table of Contents (14) Chapters Close

Preface 1. Data Science Overview FREE CHAPTER 2. SQL Server 2017 as a Data Science Platform 3. Data Sources for Analytics 4. Data Transforming and Cleaning with T-SQL 5. Data Exploration and Statistics with T-SQL 6. Custom Aggregations on SQL Server 7. Data Visualization 8. Data Transformations with Other Tools 9. Predictive Model Training and Evaluation 10. Making Predictions 11. Getting It All Together - A Real-World Example 12. Next Steps with Data Science and SQL 13. Other Books You May Enjoy

Working with XML data

SQL Server is more than capable of working with XML data. Since the 2005 version, it's actually one of the supported data types, which allows you to store up to 2 GB of XML content per record. When you type a query for SQL Server, the query returns data as a rowset—set of rows and columns. But you can retrieve all the data as an XML document too. You can add a special clause to the query, FOR XML, which will render the result as an XML document instead of the result set.

When you would like to create a XML document as a result of your query, you can use four different modes to render the XML file. These are as follows:

  • Auto
  • Path
  • Explicit
  • Raw

The raw mode will just generate an element representing a row from the result set. In this mode, each line will be used to build an element named <row>, with attributes representing the columns from...

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