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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 FREE CHAPTER 2. The Basics of SQL for Analytics 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

Relational databases are a mature and ubiquitous technology that is used to store and query data. Relational databases store data in the form of relations, also known as tables, which allow for an excellent combination of performance, efficiency, and ease of use. SQL is the language used to access relational databases. SQL is a declarative language that allows users to focus on what to create, as opposed to how to create it. SQL supports many different data types, including numeric data, text data, and even data structures.

When querying data, SQL allows a user to pick which fields to pull, as well as how to filter the data. This data can also be ordered, and SQL allows for as much or as little data as we need to be pulled. Creating, updating, and deleting data is also fairly simple and can be quite surgical.

Now that we have reviewed the basics of SQL, we will discuss how SQL can be used to perform the first step in data analytics, cleaning, and the transformation of...

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