SQL for Data Analysis

Chapter 1. Analysis with SQL

If you’re reading this book, you’re probably interested in data analysis and in using SQL to accomplish it. You may be experienced with data analysis but new to SQL, or perhaps you’re experienced with SQL but new to data analysis. Or you may be new to both topics entirely. Whatever your starting point, this chapter lays the groundwork for the topics covered in the rest of the book and makes sure we have a common vocabulary. I’ll start with a discussion of what data analysis is and then move on to a discussion of SQL: what it is, why it’s so popular, how it compares to other tools, and how it fits into data analysis. Then, since modern data analysis is so intertwined with the technologies that have enabled it, I’ll conclude with a discussion of different types of databases that you may encounter in your work, why they’re used, and what all of that means for the SQL you write.

What Is Data Analysis?

Collecting and storing data for analysis is a very human activity. Systems to track stores of grain, taxes, and the population go back thousands of years, and the roots of statistics date back hundreds of years. Related disciplines, including statistical process control, operations research, and cybernetics, exploded in the 20th century. Many different names are used to describe the discipline of data analysis, such as business intelligence (BI), analytics, data science, and decision science, and practitioners have a range of job titles. Data analysis is ...