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. Using SQL to Uncover the Truth: A Case Study

4. Aggregate Functions for Data Analysis

Activity 4.01: Analyzing Sales Data Using Aggregate Functions


  1. Open pgAdmin, connect to the sqlda database, and open SQL query editor.
  2. Calculate the total number of unit sales the company has made:

The result is as follows:

Figure 4.29: Result of COUNT(*) for sales units

Note that because each sales transaction contains a product ID, there is no NULL value in the product_id column. So, COUNT(product_id) will also work. Similarly, COUNT(sales_amount) will also work.

  1. Calculate the total sales amount in dollars for each state:
      sales s
      customers c
      s.customer_id = c.customer_id

The result is as follows:

Figure 4.30: Result of sales by state

  1. Identify the top five best dealerships in terms of the most units...