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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

Summary

In this chapter, you learned how to interface your database with other analytical tools for further analysis and visualization. While SQL is powerful, there will still be those odd analyses that need to be undertaken in other systems. To solve this problem, SQL allows you to transfer data in and out of the database for whatever tasks you may require.

Initially, we looked at how you can use the psql command-line tool to query a database. From there, we were able to explore the COPY command and the psql-specific \COPY command, which enabled you to import and export data to and from the database in bulk. Next, you looked at programmatically accessing the database using analytical software such as Python. From there, you were able to explore some of the advanced functionality in Python, including SQLAlchemy and pandas, which enabled you to perform data manipulation and visualization using a programming language.

In the next chapter, you will examine data structures that...

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