As much as we all wish numbers could speak for themselves, they do not. That means it is our job to ensure they have a voice. Because of this, I chose to focus my attention on Chapter 6 in the book, Data Points: Visualization That Means Something by Nathan Yau. This section is titled “Designing For an Audience” and focuses on common mistakes made presenting data to varying audiences. Throughout the chapter Yau highlights common flaws among visualizations. He then goes on to provide solutions to fix the graphs and charts. The chapter then closes by reminding statisticians that numbers do not lie, only incorrectly used data does and it is our responsibility to share the truth.

In order to do so, we must ensure that we are educating ourselves. Just because someone can make a pretty graph, does not mean they can make a good graph. Too much data confuses viewers, and too much decoration distracts them. You also have to know how to size things based on your audience. Is it a small classroom or large auditorium? Good visualizations are all about finding balance.

This is a skill that is often overlooked in the pursuit of innovation. There have been many times where someone presenting data wants to make a fun and creative display. This however can lead to a poor representation of the information. One piece of advice given by Yau is “Novel graphics are fine, but don’t make them hard to read or nonsensical for the sake of uniqueness. Instead, make use of the uniqueness or relevance of your data.” The main example of this in the text was the periodic table. It provides an effective and unique way to display the elements but would not have the same effect on a different dataset. 

Viewing this from a consulting perspective, this practice becomes even more critical. Business owners will all have varying knowledge on data and some of them will not even care about the numbers, just what it means for them. Businesses have to make many quick, informed decisions to remain competitive. Good data visualizations play a large role in that. 

Many people overlook the traditional forms of visualizations like pie charts and histograms because they are not flashy. They forget that these are the traditional forms because they are easy to understand. With proper labeling and design, the viewer needs very little knowledge to comprehend. After establishing a basic graph, we can then take a step back and examine our data. What does it say? What do we want it to highlight? How can we use it to help the client? 

Looking to the future, I plan to pursue a career in consulting and marketing. After reading this chapter I have a deeper understanding of what is important to consider in this field. Data literacy cannot always be expected from those you work with, so learning to adapt and adjust now will be a great strength in the future. This reading was a useful reminder to “Learn all you can about your data, and design your graphics based on those findings. After that, the smaller things tend to fall in place.”