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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
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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

Summary

The chapter provided a guide on updating data in databases with the UPDATE statement, transforming data using PostgreSQL functions, creating user-defined functions with the CREATE FUNCTION statement, and changing table definitions with the ALTER statement. With this knowledge, you will be able to manipulate existing data and existing table structure to adapt to the changes in the real world. You will also be able to apply complex transformations with either system functions or your own functions.

At this point, you have learned how to work on each table within the CRUD lifecycle. You can create and drop the tables, insert or copy data, transform and update data, and alter the table structure, against a single table. Starting from the next chapter, you will look at the interactions between tables, as well as further aggregation from the raw tables.

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