2.1 Why Visualize Data?

In the previous chapter, Exploratory Data Analysis (EDA) was introduced as the fundamental building block for nearly all types of more complicated analysis.  Whereas Chapter 1 focused primarily on EDA aspects such as the generation and analysis of summary statistics, this chapter will dive into data visualization, the other core component of EDA.  

Data visualization is one of the most fundamentally important elements of your “toolkit” as an analytics professional.  Regardless of whether you are a complete data analytics novice, or a master with decades of experience in the field, the time you invest in your data visualization skill development will pay big dividends.

If you are already working full-time, improving your visualization skills can help to make you irreplaceable to your team (especially if no one else on the team can create them as well as you can!)

If you are currently looking for a job in analytics, visualization “up-skilling” can help you, too.  As part of your interviewing/hiring process, you may be asked by a company to analyze and report on a sample dataset.  If you can wow the audience with some well-designed, informative data visualizations, you are certain to leave a lasting, positive impression with the interview panel.  

Data visualizations have a wide appeal, in a way that summary statistics often do not.  If you start telling a general interest audience that “sales in Q3 have exceeded our 10-quarter trailing average by more than 1.5 standard deviations” you might just get some puzzled looks.  However, if you can express that difference through a simple visualization, you may be able to “tell the story” in a way that doesn’t require arcane statistical knowledge.  

As we examine various visualizations throughout this chapter, keep in mind that data visualization is just as likely to generate more questions about the data as it is to deliver answers.  We cannot establish cause-and-effect from visualizations – we can only do this with valid, controlled experiments.