Data Analysis Using SQL and Excel, 2nd Edition

CHAPTER 1 A Data Miner Looks at SQL

Data is being collected everywhere. Every transaction, every web page visit, every payment—and much more—is filling databases, relational and otherwise, with raw data. Computing power and storage have grown to be cost effective, a trend where today’s smart phones are more powerful than supercomputers of yesteryear. Databases are no longer merely platforms for storing data; they are powerful engines for transforming data into useful information about customers and products and business practices.

The focus on data mining has historically been on complex algorithms developed by statisticians and machine-learning specialists. Once upon a time, data mining required downloading source code from a research lab or university, compiling the code to get it to run, and sometimes even debugging it. By the time the data and software were ready, the business problem had lost urgency.

This book takes a different approach because it starts with the data. The billions of transactions that occur every day—credit cards swipes, web page visits, telephone calls, and so on—are now often stored in relational databases. Relational database engines count among the most powerful and sophisticated software products in the business world, so they are well suited for the task of extracting useful information. And the lingua franca of relational databases is SQL.

The focus of this book is more on data and what to do with data and less on theory. Instead of trying to ...