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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 JSON

JSON, or JavaScript Object Notation, is a popular format these days for exchanging data among various endpoints. The most common usage of JSON is on mobile and web services. JSON is also used to store data for NoSQL databases, such as the Azure Cosmos DB. While it might seem that, with NoSQL and JSON, we work with unstructured data, only it's actually not the case. The data has a structure, only it's schema agnostic and the storage schema is defined by JSON itself, based on the content.

SQL Server has supported working with JSON since SQL Server 2016. Unlike XML, however, JSON is not the native data type in SQL Server. You can, however, use many SQL Server functions and operators to work with JSON text and perform the following:

  • Parse JSON text, and read or modify values
  • Transform arrays of JSON objects into a table format
  • Run any Transact-SQL query...
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