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SQL for Data Analytics

You're reading from   SQL for Data Analytics Harness the power of SQL to extract insights from data

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781801812870
Length 540 pages
Edition 3rd Edition
Languages
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Authors (4):
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Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
Matt Goldwasser Matt Goldwasser
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Matt Goldwasser
Jun Shan Jun Shan
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Jun Shan
Upom Malik Upom Malik
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Upom Malik
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Toc

Table of Contents (11) Chapters Close

Preface 1. Understanding and Describing Data 2. The Basics of SQL for Analytics FREE CHAPTER 3. SQL for Data Preparation 4. Aggregate Functions for Data Analysis 5. Window Functions for Data Analysis 6. Importing and Exporting Data 7. Analytics Using Complex Data Types 8. Performant SQL 9. Using SQL to Uncover the Truth: A Case Study Appendix

The COPY Command

At this point, you are probably familiar with the SELECT statement (covered in Chapter 2, The Basics of SQL for Analytics), which allows you to retrieve data from a database. While this command is useful for small datasets that can be scanned quickly, you will often want to save a large dataset to a file. By saving these datasets to files, you can further process or analyze the data locally using Excel or Python. To retrieve these large datasets, you can use the PostgreSQL COPY command, which efficiently transfers data from a database to a file, or from a file to a database. This COPY command must be executed when connected to the PostgreSQL database using a SQL client, such as the PostgreSQL psql command. In the next section, you will learn how to use the psql command, then you will learn how to copy data with it.

Running the psql Command

You have been using the pgAdmin frontend client to access your PostgreSQL database, and you have briefly used the psql tool...

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