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


In this chapter, you learned how to interface your database with other analytical tools for further analysis and visualization. While SQL is powerful, there will still be those odd analyses that need to be undertaken in other systems. To solve this problem, SQL allows you to transfer data in and out of the database for whatever tasks you may require.

Initially, we looked at how you can use the psql command-line tool to query a database. From there, we were able to explore the COPY command and the psql-specific \COPY command, which enabled you to import and export data to and from the database in bulk. Next, you looked at programmatically accessing the database using analytical software such as Python. From there, you were able to explore some of the advanced functionality in Python, including SQLAlchemy and pandas, which enabled you to perform data manipulation and visualization using a programming language.

In the next chapter, you will examine data structures that...