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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
Author Profile Icon Benjamin Johnston
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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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

Introduction

In Chapter 7, Analytics Using Complex Data Types, you learned the necessary skills to effectively analyze data within a SQL database. In this chapter, you will turn your attention to the efficiency of this analysis, investigating how you can increase the performance of SQL queries. Efficiency and performance are key components of data analytics. Without considering these factors, physical constraints, such as time and processing power, can significantly affect the outcome of an analysis.

In this chapter, you will first learn the different ways PostgreSQL performs query planning, in which the PostgreSQL database evaluates the SQL statement and underlying physical implementation and decides how to execute this SQL. You will learn the most basic way of retrieving data, which is scanning by sequence. You will then learn the concept of an index and the two most common indexes in PostgreSQL, the B-tree index and the hash index. From there, you will learn how to kill long...

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