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

The HAVING Clause

We can now perform all sorts of aggregate operations using GROUP BY. Sometimes, though, certain rows in aggregate functions may not be useful, and you may want to remove them from the query output. For example, when doing the customer counts, perhaps you are only interested in places that have at least 1,000 customers. Your first instinct may be to write something such as this:

  state, COUNT(*)

However, you will find that the query does not work and gives you the following error:

Figure 3.13: Error showing the query not working

In order to use the filter on aggregate functions, you need to use a new clause: HAVING. The HAVING clause is similar to the WHERE clause, except it is specifically designed for GROUP BY queries. The general structure of a GROUP BY operation with a HAVING statement is as...