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Dona Wong is one of the few data visualization wizards who can make complex financial data simple and interesting. After a few information graphics stints at prestigious news organizations such as The New York Times and The Wall Street Journal, Dona has gained very deep expertise in one of the most daunting tasks in data visualization: complex financial data.
Dona studied information design at Yale under tutelage of the Edward Tufte who famously pioneered modern day data visualization. Dona’s two decades of visual journalism expertise with a focus on business data was condensed into her book The Wall Street Journal Guide to Information Graphics, which talks about the dos and don’ts in financial chart making.
Today, Dona is vice president of Digital Strategy at the Federal Reserve Bank of New York where she oversees the Bank’s digital presence for the web, mobile, social media, video storytelling and data visualization. We recently reached out to Dona for her deep insights on visualizing financial data, so that you can produce better business graphics too.
A lot of our users see the need to visualize financial/business data because no one wants to read lengthy reports anymore. Given your expertise in financial data visualization, what is your approach to choosing the best format to visualize a dataset that makes financial report simple yet interesting?
The principle of visualizing data is the same, whether they are financial or medical charts. Graphics are either effective or ineffective. I had the opportunity to study under the tutelage of Edward Tufte at Yale University, a pioneer in data visualization. I’ve learned that data visualization is a powerful tool for revealing unexpected patterns and anomalies to our audience.
Part of my thesis was to map the location of emergency phones in relation to crime statistics on the Yale campus. The juxtaposition of the two data sets — emergency phone locations and crime statistics — created a whole new meaning that was not there before. We can now answer the question: Are emergency phones available at high crime locations? Already in my early studies, I’ve learned that information graphics can be literally a matter of life or death.
Visualizing data is not the end of the process, we still need to present the story. How do you craft a story based on these data visuals in a way that truly engage our audience?
Data visualization is about telling a good story. In any story, content comes first. The essential elements of good information graphics are:
“Rich content brings meaning to a graphic.
Inviting visualization interprets the content and highlights the essence of the information for the reader.
Sophisticated execution brings the content and the graphics to life.”
excerpt from The Wall Street Journal Guide to Information Graphics.
What is your suggestion on visualizing massive amount of qualitative data?
One of the most important element in data stories is relevancy. We are inundated with data or content, be it qualitative or quantitative. Our content needs to be mapped to a clear objective with a targeted audience. The question is not “How much content?” Rather, we want to answer “How useful is the information?”
From my days as graphics editor at The New York Times and head of graphics at The Wall Street Journal, I learned the audience is the most important group of people in my work. Having millions of readers means having millions of critics on a daily basis. Understanding my audience helps shape my graphic.
For example, a lab report with clear illustrated graphics about blood pressure and cholesterol level can motivate patients to exercise more and change their diet. However, if the graphics are overly complicated, the report is not only useless, it is a disservice to the patients. We have to take the perspective of our audiences and approach the solution with conviction and empathy, as well as accuracy.
There is so much data that is available to us for every single subject matter. It’s overwhelming. How do you select data sufficient to tell a story but not too much that the audience get overwhelmed?
Everyone talks about big data. The real story is in the small data. It requires balancing the discipline of data analysis and succinct storytelling to visualize the data and turn it into actionable insights.
The question we need to ask is how do we actually use data visualization to present the data in a way that provides insights to our audience to meet any organizational or business challenges. Data visualization is a means to an end, and not an end in itself.
What is the most common pitfall in presenting data?
Color should be used to differentiate hierarchy of information. Everyone can perceive the difference in shading, but they may not differentiate certain colors.
“Color combinations such as red/green … can be similar in value or lightness. The lack of contrast in lightness makes it virtually unreadable for color-blind users.” — excerpt from The Wall Street Journal Guide to Information Graphics.
And yet, we see these faulty color combinations all the time. The key is to develop a charting color palette with multiple shades of the same hue. According to the National Institutes of Health, about 1 in 10 men have some form of colorblindness. Do you want your message to get lost?
* The views expressed here are her own and do not necessarily represent those of the Federal Reserve Bank of New York.
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We will bring more expert content like this Q&A with Cole above. Stay tuned!