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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

Exchanging Data Using COPY

In the previous chapter, you learned about the SQL CREATE, INSERT, and DROP operations in the CRUD process. You also learned how to populate the created tables with manually written values or values from other tables. These operations are good enough to work on small datasets inside a database. However, in real-world scenarios, the bulk of the data comes from systems outside of the database. For example, different systems within the same company need to exchange data, and business analysts need to utilize data from external vendors for analytics. This data is usually sent in the form of files. In addition, once you finish your analytical tasks, you also need to share your results with internal teams or external customers. This data sharing is often done using files, too. While it is possible to use SQL statements to read from or write to these files, they are generally slow and are limited in file processing power.

Typically, data transfer is done with...

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