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SQL for Data Analytics

You're reading from   SQL for Data Analytics Analyze data effectively, uncover insights and master advanced SQL for real-world applications

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Product type Paperback
Published in Nov 2025
Publisher Packt
ISBN-13 9781836646259
Length 336 pages
Edition 4th Edition
Languages
Tools
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Authors (5):
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Jun Shan Jun Shan
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Jun Shan
Benjamin Johnston Benjamin Johnston
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Benjamin Johnston
Haibin Li Haibin Li
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Haibin Li
Matt Goldwasser Matt Goldwasser
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Matt Goldwasser
Upom Malik Upom Malik
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Upom Malik
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1: Data Management Systems
2. Introduction to Data Management Systems FREE CHAPTER 3. Creating Tables with Solid Structures 4. Exchanging Data Using COPY 5. Manipulating Data with Python 6. Part 2: Data Presentation and Manipulation
7. Presenting Data with SELECT 8. Transforming and Updating Data 9. Defining Datasets from Existing Datasets 10. Aggregating Data with GROUP BY 11. Inter-Row Operation with Window Functions 12. Part 3: Advanced Topics on Analytics
13. Performant SQL 14. Processing JSON and Arrays 15. Advanced Data Types: Date, Text, and Geospatial 16. Inferential Statistics Using SQL 17. A Case Study for Analytics Using SQL 18. Unlock Your Exclusive Benefits 19. Other Books You May Enjoy
20. Index

Processing JSON and Arrays

You have already seen two different ways of recording data in Chapter 1, using the JavaScript Object Notation (JSON) document model and using the relational model. You have also seen that JSON is a natural way of recording real-world data, but the relational model provides a much simpler approach for most use cases. That’s why all the data processing you have learned about so far is SQL statements, which only handle relational data.

It must be pointed out, however, that JSON is still a convenient way of describing real-world issues. As such, modern SQL does support complex data structures such as JSON and arrays. These data structures are a natural way of data description and show up constantly in technology applications. Being able to use them in a database makes it easier to perform many kinds of analysis work.

The following topics are covered in this chapter:

  • Understanding types of data
  • Using JSON
  • Using arrays
  • ...
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