Preface | SQL for Data Analytics

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SQL for Data Analytics - Third Edition

By : Jun Shan, Matt Goldwasser , Upom Malik , Benjamin Johnston

4.8 (53)

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SQL for Data Analytics

4.8 (53)

By: Jun Shan, Matt Goldwasser , Upom Malik , Benjamin Johnston

Buy this Book

Overview of this book

Every day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience. You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation. By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.

Preface

About the Book

About the Authors

Audience

About the Chapters

Conventions

Setting up Your Environment

Installing Git

Loading the Sample Datasets – Windows

Loading the Sample Datasets – Linux

Loading the Sample Datasets – macOS

Running SQL files

Accessing the Code Files

1. Understanding and Describing Data

Introduction

Data Analytics and Statistics

Types of Statistics

Working with Missing Data

Statistical Significance Testing

SQL and Analytics

Summary

Free Chapter

2. The Basics of SQL for Analytics

Introduction

The World of Data

Relational Databases and SQL

PostgreSQL Relational Database Management System (RDBMS)

Creating Tables

Basic Data Types of SQL

Data Structures: JSON and Arrays

Column Constraints

Updating Tables

SQL and Analytics

Summary

3. SQL for Data Preparation

Introduction

Assembling Data

Cleaning Data

Transforming Data

Summary

4. Aggregate Functions for Data Analysis

Introduction

Aggregate Functions

Aggregate Functions with the GROUP BY Clause

Aggregate Functions with the HAVING Clause

Using Aggregates to Clean Data and Examine Data Quality

Summary

5. Window Functions for Data Analysis

Introduction

Window Functions

Statistics with Window Functions

Window Frame

Summary

6. Importing and Exporting Data

Introduction

The COPY Command

Using Python with your Database

Going Passwordless

Summary

7. Analytics Using Complex Data Types

Introduction

Date and Time Data types for Analysis

Performing Geospatial Analysis in PostgreSQL

Using Array Data types in PostgreSQL

Using JSON Data types in PostgreSQL

Text Analytics Using PostgreSQL

Summary

8. Performant SQL

Introduction

The Importance of Highly Efficient SQL

Database Scanning Methods

Killing Queries

Functions and Triggers

Summary

9. Using SQL to Uncover the Truth: A Case Study

Introduction

Case Study

Summary

Appendix

1. Understanding and Describing Data

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

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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.

SQL for Data Analytics - Third Edition

By : Jun Shan, Matt Goldwasser , Upom Malik , Benjamin Johnston

SQL for Data Analytics

By: Jun Shan, Matt Goldwasser , Upom Malik , Benjamin Johnston

Overview of this book

About the Chapters

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