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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
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Matt Goldwasser
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 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

Performant Joins

The JOIN functionality in SQL-compliant databases provides a very powerful and efficient method of combining data from different sources, without the need for complicated looping structures or a series of individual SQL statements. We covered joins and join theory in detail in Chapter 3, SQL for Data Preparation. As suggested by the name of the command, a join takes information from two or more tables and uses the contents of the records within each table to combine the two sets of information. Because we are combining this information without the use of looping structures, this can be done very efficiently. In this section, we will consider the use of joins as a more performant alternative to looping structures. The following is the Customer Information table:

Figure 8.33: Customer information

The following table shows the Order Information table:

Figure 8.34: Order information

So, with this information, we may want...

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