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  • Book Overview & Buying SQL for Data Analytics
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SQL for Data Analytics

SQL for Data Analytics

By : Upom Malik, Matt Goldwasser, Benjamin Johnston
3.5 (35)
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SQL for Data Analytics

SQL for Data Analytics

3.5 (35)
By: Upom Malik, Matt Goldwasser, Benjamin Johnston

Overview of this book

Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don't know how to use it to gain the most effective business insights from data, this book is for you. SQL for Data Analytics helps you build the skills to move beyond basic SQL and instead learn to spot patterns and explain the logic hidden in data. You'll discover how to explore and understand data by identifying trends and unlocking deeper insights. You'll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you'll learn how to increase your productivity with the help of profiling and automation. By the end of this book, you'll be able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of an analytics professional. Please note: if you are having difficulty loading the sample datasets, there are new instructions uploaded to the GitHub repository. The link to the GitHub repository can be found in the book's preface.
Table of Contents (11 chapters)
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9
9. Using SQL to Uncover the Truth – a Case Study

Aggregate Functions

With data, we are often interested in understanding the properties of an entire column or table as opposed to just seeing individual rows of data. As a simple example, let's say you were wondering how many customers ZoomZoom has. You could select all the data from the table and then see how many rows were pulled back, but it would be incredibly tedious to do so. Luckily, there are functions provided by SQL that can be used to do calculations on large groups of rows. These functions are called aggregate functions. The aggregate function takes in one or more columns with multiple rows and returns a number based on those columns. As an illustration, we can use the COUNT function to count how many rows there are in the customers table to figure out how many customers ZoomZoom has:

SELECT COUNT(customer_id) FROM customers;

The COUNT function will return the number of rows without a NULL value in the column. As the customer_id column is a primary key and cannot...

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SQL for Data Analytics
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