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

1. Understanding and Describing Data

Activity 1.01: Classifying a New Dataset


  1. The unit of observation is a car sale.
  2. Date and Sales Amount are quantitative, while Make is qualitative.

While there could be many ways to convert Make into numeric data, one commonly accepted method would be to map each of the Make types to a number. For instance, Ford could map to 1, Honda could map to 2, Mazda could map to 3, Toyota could map to 4, Mercedes could map to 5, and Chevy could map to 6.

Activity 1.02: Exploring Dealership Sales Data


  1. Open Microsoft Excel to a blank workbook.
  2. Go to the Data tab and click on Get Data | From File | From Text/CSV.
  3. Find the path to the dealerships.csv file and click on Import.
  4. In the file import window, click on Load. The following table is what you will see when the file loads.

Figure 1.38: The dealerships.csv file loaded

A histogram of the results may vary a little...