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Stories by the Number


I was recently scanning LinkedIn and stumbled upon an article about the best tech cities. Included as part of the article was this graph:

There’s a ton of data in this graph. Each city is ranked on a scale on six different characteristics that reflect technology friendliness, according to Savills research. While visually pleasing, I had difficulty understanding the graph. I know New York tops the list, but how does it compare with Austin on “Talent Pool”? How does Copenhagen compare with Singapore on “City Buzz/Wellness”? I wanted to find out, so a friend and I created a new version of the graph, utilizing Tableau Software:

You can view the whole chart here.

Stuart Read spoke this week in PACE about creating a story with our data. Data visualization, when executed correctly and thoughtfully, can look like a piece of art while simultaneously simplifying complex sets of data. Perhaps even more importantly, however, data visualization can tell intriguing stories about the world we live in. The chart below, for example, shows migration to Oregon from across the U.S over the years:

You can interact with the charts here to see where people in every U.S. state are from and where they moved to over the years.

Even something as seemingly mundane as what we call our fizzy beverages across the U.S. can be conveyed persuasively with the right type of graph:

Who knew usage of the term “pop” stretched from Washington and Oregon all the way through the Midwest?! If I were a marketing associate in New York City, I could use this graph to convince executives to label our drink “pop” instead of “soda” in Oregon television commercials.

As you think about your own data story, appreciate that each of these data visualizations contains three core elements:

Clear. Good visualizations are simple enough to be instantly understood by someone unfamiliar with the data. In order to accomplish this level of succinctness, you first have to decide on one or more insights you want to expose in the data, then choose a graph that will best convey your main point(s).

Creative. Each of the visualizations in this article went beyond the simple graphs we all learned in elementary school. Bar graphs, scatter plots, and line graphs serve a purpose, but there are tons of great tools now to create more interesting visualizations! Power BI, Google charts, Tableau, Plotly, Datawrapper–the list goes on and on. Some programs even give their software free to students.

Targeted. Good data visuals are tailored to the audience. Just like you would tailor a presentation style to an audience, so should the visuals.

Data visualization is hard to get right, but when you do, the results are very rewarding. Similar to an author selecting words for their next novel, data visualization requires careful choice of type, color, and complexity. Great data visualization takes complicated, messy numbers and creates an easily understandable, interactive, and beautiful piece of art that tells a story.


Works Cited

Aisch, Gregor, Robert Gebeloff, and Kevin Quealy. “Where We Came From and Where We Went, State by State.” The New York Times, 19 Aug. 2014. Accessed 23 Feb. 2019.

Fink, Elissa. “Do You Say Coke, Soda, or Pop? A Map Visualization Shows Your Likely Answer.” Tableau, 24 Aug. 2008. Accessed 22 February 2019.

Nguyen, Kelli, Scott Olster, and Andrew Seaman. “NYC outranks SF as best tech city, why Earth may run out of humans, and more top insights.” LinkedIn Daily Rundown, 9 Feb. 2019. Accessed 14 Feb. 2019.

Emily Anderson is a first-year MBA candidate at Willamette University. She is a 2017 graduate of Gonzaga University, where she received her B.A. in International Studies. Emily enjoys PACE because of the opportunity to learn valuable career information, improve her analytical and speaking skills, and build partnerships with not-for-profits in Oregon.



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