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)
Preface
7
7. The Scientific Method and Applied Problem Solving

Using Aggregates to Clean Data and Examine Data Quality

In Chapter 1, Introduction to SQL for Analytics, we discussed how SQL can be used to clean data. While the techniques mentioned in that chapter do an excellent job of cleaning data, aggregates add a number of techniques that can make cleaning data even easier and more comprehensive. In this section, we will look at some of these techniques.

Finding Missing Values with GROUP BY

As we mentioned in Chapter 1, Introduction to SQL for Analytics, one of the biggest issues with cleaning data is dealing with missing values. Although we discussed how to find missing values and how we could get rid of them, we did not say too much about how we could determine the extent of missing data in a dataset. Primarily, this was because we did not have the tools to deal with summarizing information in a dataset – that is, until this chapter.

Using aggregates, identifying the amount of missing data can tell you not only which...