Book Image

The Applied SQL Data Analytics Workshop - Second Edition

By : Matt Goldwasser, Upom Malik, Benjamin Johnston
3.5 (2)
Book Image

The Applied SQL Data Analytics Workshop - Second Edition

3.5 (2)
By: 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. Hidden in this data are key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level. Are you ready to enter the exciting world of data analytics and unlock these useful insights? Written by a team of expert data scientists who have used their data analytics skills to transform businesses of all shapes and sizes, The Applied SQL Data Analytics Workshop is a great way to get started with data analysis, showing you how to effectively sieve and process information from raw data, even without any prior experience. The book begins by showing you how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you'll learn how to write SQL queries to aggregate, calculate and combine SQL data from sources outside of your current dataset. You'll also discover how to work with different data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you'll finally 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 The Applied SQL Data Analytics Workshop, you'll have the skills you need to start identifying patterns and unlocking insights in your own data. You will be capable of looking and assessing data with the critical eye of a skilled data analyst.
Table of Contents (9 chapters)
7. The Scientific Method and Applied Problem Solving

Aggregate Functions with GROUP BY

So far, we've used aggregate functions to calculate statistics for an entire column. However, often, we are not interested in the aggregate values for a whole table, but for smaller groups in the table. To illustrate this, let's go back to the customers table. We know that the total number of customers is 50,000. However, we might want to know how many customers we have in each state. How would we calculate this?

We could determine how many states there are with the following query:


We are expected to see 52 distinct states returned as a result of the preceding query.

Once you have the list of states, you could then run the following query for each state:


Although you can do this, it is incredibly tedious and can take an incredibly long time if there...