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SQL for Data Analytics

You're reading from   SQL for Data Analytics Perform fast and efficient data analysis with the power of SQL

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789807356
Length 386 pages
Edition 1st Edition
Languages
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Authors (3):
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Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
Matt Goldwasser Matt Goldwasser
Author Profile Icon Matt Goldwasser
Matt Goldwasser
Upom Malik Upom Malik
Author Profile Icon Upom Malik
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, we learned about the power of window functions. We looked at how to construct a basic window function using OVER, PARTITION BY, and ORDER BY. We then looked at how to calculate statistics using window functions, and how to adjust a window frame to calculate rolling statistics.

In the next chapter, we will look at how to import and export data in order to utilize SQL with other programs. We will use the COPY command to upload data to your database in bulk. We will also use Excel to process data from your database and then simplify your code using SQLAlchemy.

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