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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
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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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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

SQL and Analytics

Throughout this chapter, you may have noticed the terms SQL table and dataset are interchangeable. More specifically, it should be clear that SQL tables can be thought of as datasets, rows can be considered as individual units of observation, and columns can be considered as features. If you view SQL tables in this way, you can see that SQL is a natural way to store datasets on a computer.

However, SQL can go further than just providing a convenient way to store datasets. Modern SQL implementations also provide tools for processing and analyzing data through various functions. Using SQL, you can clean data, transform data into more useful formats, and analyze a variety of statistical measures to discover interesting patterns. The rest of this book will be dedicated to understanding how SQL can be used for these purposes productively and efficiently.

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SQL for Data Analytics - Third Edition
Published in: Aug 2022
Publisher: Packt
ISBN-13: 9781801812870
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