Julie is a data analyst working for a sporting goods e-commerce site. She has responsibilities that include reporting on the site's performance. The site includes multiple site categories, such as menswear, womenswear, as well as sporting equipment and shoes. Each category requires separate reporting as well as analysis on an ad hoc basis. Julie loves her work as she has been afforded the opportunity to monitor and analyze datasets of extreme size and complexity. This, however, is also one of her biggest challenges as she has a hard time understanding data of such size and complexity. This is one of the most important challenges data visualization tackles.

By adding data visualization to her repertoire, Julie can turn her unwieldy and static text data into several charts that both drive action and convey the underlying data in a much more efficient presentation. Time trends can be noticed and understood more easily. Differences in static metrics can also be noticed. Most of all, the analyst and the viewer can more efficiently understand and act on the data. This, much like what the initial quote says, is the main reason for visualization.