I have been teaching data visualization at the University of Cincinnati for almost 8 years now. I have taught 33 classes, with 3 more this semester and nearly 1,700 students (not counting the students from this semester). The profile of the students, which will be important to understand for the topic of this post, is mostly graduate students pursuing Master of Science in Business Analytics or Master of Science in Information Technology, but there are also other degrees/majors sprinkled in, including MBA, Finance, Marketing, Arts Administration, Engineering and even Graphic Design (the last 3 being outside of the business college). There are also students pursuing a certificate in Business Analytics. Many of these students have some work experience as well. This is typically a few years of experience, possibly as a consultant, or intern or they may be pursuing a degree or certificate while they work full-time.
Prior to each semester, I review the course content, specifically the presentations, and I adjust this content. Some semesters it is just a few tweaks, but other times there are significant changes. As I look back, the content is very different from when I started, but there are also many things that have been there since the beginning of the course. One of the things that I have always included and discussed in the course material, even from the beginning of teaching this course, is Charles Joseph Minard's visualization of Napoleon's 1812 March into Russia. Edward Tufte describes this as, "Possibly the best statistical graphic ever drawn." and he has promoted and discussed this himself in his workshops and books.
It would be hard to imagine a course on data visualization that does not include at least some of the famous visualizations in the field of data visualization and Minard's graph has become one of the most famous graphs in the field. Or has it?
I have to say, I do love Minard's graph. It is one of a few visualizations that I have framed and hanging in my office. It also ties very well to my class content. I discuss the Tufte's view and then contrast that with Seth Godin's view that it's "one of the worst charts ever done" as it violates his principle of Make a Point in Two Seconds. One of the main tenets that I teach in data visualization is to ask "Who's the audience?" and "What's the message?" This is something I have also taught since the very beginning. Minard's graphic leads to a good discussion about this. For a certain audience, to illustrate a certain message, it might be "the best statistical graphic ever drawn", but if presenting this data to a board room of executives who are looking for a quick summary, it might be "one of the worst charts ever done". It really ties things together quite well, so each semester I continue to teach this content. In addition, I also teach this material in private and public workshops. I did not keep count of this, but it's fair to say that multiple thousands of people have sat through this material and I know many others that include it in their course content as well. In fact, it's part of the course curriculum for the data visualization course that I built out for Tableau and used, at least in part, by many professors teaching data visualization in higher education.
You have read this far and that was a lot of set up, but I think it's important to understand a bit about my course and the students. Here is what is fascinating to me as a data visualization professor. My students have never seen this chart. I am teaching two sections of my course right now, each with approximately 65 students, and I asked each class separately, "How many of you have seen this chart before?" In my Tuesday night class, I had two people raise their hand and in my Saturday class, I had three people raise their hand. In total, there were only five students out 130 that had seen Minard's graphic prior to my class. The numbers were even smaller when I asked, "How many of you have heard of Edward Tufte?", and in last week's class there was not a single hand raised when I asked the class, "How many of you have heard of a slopegraph?". That's right, out of ~65 students, not one of them had heard of a slopegraph.
As data visualization professionals, we can quickly take for granted what we have learned and applied over the years. We assume that everyone has surely seen Minard's graphic or Florence Nightingale's Rose Diagram. We may think to ourselves, surely they have heard of Stephen Few, Edward Tufte or Hans Rosling. And we might tire of lecturing on topics such as the preattentive attributes, the use of color and colorblindness, avoiding 3D exploding pie charts, or "rehashing" the most famous data visualizations from history. In reality, we need to step back and consider that the vast majority of our audience have not read Cleveland and McGill or Colin Ware. Most of them have not studied the basic principles of data visualization. They may not be familiar with certain chart types, like a slopegraph or sparkline, which to us are just as common a term as a bar chart.
When teaching or presenting these principles, whether it is a formal presentation or workshop, or a conversation to educate people in your office, it's important to understand that most of society does not know what you know about data visualization. You have read books, research papers and articles that they have not read. You've attended presentations and workshops that they have not attended. And you have likely been building data visualizations for many years, learning what works and what doesn't, and applying it in a real-world application; knowledge that takes years of experience to gain.
If you, as a data visualization professional, are attending a presentation or workshop, you may be listening to content you have heard a hundred times before and may have taught yourself, but realize that it's likely new content to the people around you. Take the opportunity to listen to how the presenter is presenting. You might pick up something new, possibly even something that might enhance your presentation of that material.
As a presenter, teacher or educator of this content, it is also important to present it as fresh content. Imagine going to a concert hall to listen to Beethoven's Fifth Symphony performed by a Major Symphony Orchestra. Professional musicians have played this piece countless times, my first performance was in high school. As a former musician (trumpet player), I have performed too many weddings to get an accurate count, but it's in the ballpark of 1,000 weddings. The most common wedding processional thanks to Princess Diana is Trumpet Voluntary, which I have performed for nearly 1,000 brides (and the occasional groom) walking down the aisle. Needless to say, I know the piece. However, even if I am playing this piece of music for the one thousand and sixth time, it is likely the first (and hopefully the last) time that the bride will walk down that aisle. It is one of the most special moments that someone can have in their life and they will surely remember it.
Do not lose sight of this as you present, teach and educate people on data visualization. What may seem boring and repetitive discussion to you, is likely brand new and fresh content to the majority of others. It is always good to refresh and refine your content, but even if it is the same content that you end up presenting over and over again, keep in mind that it may very well be the first time your audience is hearing it.
I hope you find this information useful. If you have any questions feel free to email me at Jeff@DataPlusScience.com
