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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

Functions and Triggers

So far in this chapter, we have discovered how to quantify query performance via the query planner, as well as the benefits of using joins to collate and extract information from multiple database tables. In this section, we will construct reusable queries and statements via functions, as well as automatic function execution via trigger callbacks. The combination of these two SQL features can be used to not only run queries or re-index tables as data is added to/updated in/removed from the database, but also to run hypothesis tests and track the results of the tests throughout the life of the database.

Function Definitions

As in almost all other programming or scripting languages, functions in SQL are contained sections of code, which provides a lot of benefits, such as efficient code reuse and simplified troubleshooting processes. We can use functions to repeat/modify statements or queries without re-entering the statement each time or searching...

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