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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

About the Chapters

Chapter 1, Understanding and Describing Data, helps you learn the basics of data analytics. You will learn how to form hypotheses and generate descriptive statistics that can provide insights into your data. You will achieve this goal by using mathematical and graphical techniques to analyze data with Excel.

Chapter 2, The Basics of SQL for Analytics, helps you learn the basics of SQL in the world of data and CRUD operations. You will learn how to use basic SQL to manipulate data in a relational database.

Chapter 3, SQL for Data Preparation, shows you how to clean and prepare data for analysis using SQL techniques. You will begin by learning how to combine multiple tables and queries into a dataset before moving on to more advanced materials.

Chapter 4, Aggregate Functions for Data Analysis, covers SQL's aggregate functions, which are powerful techniques for summarizing data. You will be able to apply these functions to generate descriptive statistics and learn how to aggregate data across all rows and break out subpopulations for further analysis.

Chapter 5, Window Functions for Data Analysis, covers SQL's window functions, which take order into account for a group of data. You will be able to apply these functions to gain new insights into data and gain important knowledge about the data, such as orders and ranks.

Chapter 6, Importing and Exporting Data, provides you with the skills required to interact with your database from other software tools (such as Python).

Chapter 7, Analytics Using Complex Data Types, gives you a rich understanding of the various data types available in SQL and shows you how to extract insights from datetime data, geospatial data, arrays, JSON, and text.

Chapter 8, Performant SQL, helps you optimize your queries so that they run faster. In addition to learning how to analyze query performance, you will also learn how you can use additional SQL functionality, such as functions and triggers, to expand the default functionality.

Chapter 9, Using SQL to Uncover the Truth: A Case Study, reinforces your acquired skills to help you solve real-world problems outside of those described in this book. Using the scientific method and critical thinking, you will be able to analyze your data and convert it into actionable tasks and information.

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