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

Window Functions

Continuing with the discussion on Window Functions, you want to find the earliest customers for ZoomZoom. In a more technical term, this means you want to rank every customer according to the date they became a customer, with the earliest customer being ranked 1, the second-earliest customer being ranked 2, and so on. You can get all the customers using the following query:

  customer_id, first_name, last_name, date_added

The result is:

Figure 5.1: Customers ordered by date_added

You can order the customers from the earliest to the most recent, copy the output to an Excel spreadsheet, and assign a row number to each row so that you have the rank for each customer. But this is not automatic and is prone to errors. SQL provides several ways using which you can achieve it. Later in this chapter, you will learn how to assign numbers to ordered records by using...