Book Image

SQL for Data Analytics - Third Edition

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

SQL for Data Analytics - Third Edition

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

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.
Table of Contents (11 chapters)
9
9. Using SQL to Uncover the Truth: A Case Study

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.