Tableau Community Spotlight: An Interview with Allen Hillery

Allen Hillery Bio

My name is Allen Hillery and I’m an adjunct associate at Columbia University at the School of Professional Studies’ Applied Analytics Program where I teach Storytelling with Data. I’m a freelance writer as well as writer at Nightingale a Medium Publication of the Data Visualization Society. I have a Bachelor’s of Engineering Degree in Civil Engineering from the City College of New York and a Master’s of Science in Management Information Systems from Baruch College. I’ve spent 20 years in the data-sphere doing data reporting, analytics and storytelling supporting sales and marketing teams and providing insights to drive the business. I also curate a LinkedIn article series that focuses on the importance of creating data narratives and spotlighting notable figures on how their use of storytelling made major impacts on society.

Twitter: @aldatavizguy


Michael: Hello, Allen. You have a passion for storytelling. Can you tell my readers why storytelling is so important to how we convey the meaning of data?

Allen: Hi Michael – Numbers alone are not memorable. Messages delivered as stories can be up to 22X more memorable than just facts. Telling a compelling story around your data helps the audience make decisions about your findings or argument easier. People are persuaded about how something made them feel in addition to just reading the facts. That’s why a narrative + visuals + data is ideal.

Michael: You teach a Storytelling with Data class at Columbia University. Can you talk a bit about the structure of the class and the kinds of activities you have your students do?

Allen: Sure, our class is set up to model how a student would encounter a project in the real world. There are a series of assignments throughout the semester that build on top of each other. A student at the start of the semester picks a company and highlights a business problem to focus on. They submit a memo as their initial assignment to the chief analytics officer identifying the need to look further into this problem. The sequence of these assignments continue with a proposal brief, storyboard, infographic and concluding with a persuasive presentation to the CEO. Throughout this experience, the student is developing a deliverable to various audiences such as the Chief Analytics Officer, Chief Marketing Officer and the CEO. Each audience has a varying degree of data literacy and this is where you learn to develop writing a focused and concise message as well as how far to go into the technical details. Most importantly, the goal is to derive insights from the data and display that in a way that captures the audience’s attention.

Michael: You also have a strong passion for data literacy. Can you tell my readers what data literacy is and why it is important?

Allen: Data literacy is the ability to read, understand, create and communicate data as information. I believe today’s abundance of data combined with how companies are operating more and more online that the workforce has to become more comfortable working with data. I like how Chartio puts it, “The world has gotten really good at collecting data, now the largest bottleneck is our ability to understand the data and make informed decisions based on it.” 

“The world has gotten really good at collecting data, now the largest bottleneck is our ability to understand the data and make informed decisions based on it.” 


There is a gap when it comes to analyzing data to derive insights. As data analytics tools become more interactive and less coding is needed, this is a perfect opportunity for less technical employees to increase their data literacy. You don’t have to be a data scientist to become data literate. Companies like AirBnB are creating data schools to upskill all levels of their workforce in data. Another growing trend we’re seeing is tech companies like Tableau hiring employees with liberal arts backgrounds. These majors are helping to smooth over the bump at the last mile of the data road by using their critical thinking skills as well as context setting. Check out my article here

Michael: Can you tell me three of your favorite storytelling tips and tricks?


  1. Remember that numbers alone are not memorable. Data visuals are key.
  2. Make sure your story has a beginning, middle and end.
  3. When presenting to a business audience make sure that you are walking through an explanatory analysis and not an exploratory analysis. You want to show off your best pearls not describe how you hunted for oysters.

Michael: Can you tell my readers a little bit about Nightingale and The Data Visualization Society?

Allen: Nightingale is a Data Visualization Journal that I believe to be groundbreaking the data viz space. It’s a testament to what I’ve been saying about data being everywhere and impacting so many facets of life from sports, social justice, business and life in general. The publication has been fortunate to interview or get contributions from a lot of popular figures in the space from Giorgia Lupi, Alberto Cairo to Catherine D’Ignazio. I’ve enjoyed contributing pieces that I categorize as data humanism. It’s important to me that everyone realizes how prevalent data is in our lives and that a lot of people who work in the space like myself are everyday people with unconventional career paths. 

Data Visualization Society (DVS) is the overarching community that houses Nightingale. Nightingale is just one facet of DVS. We have a variety of slack channels where people can discuss topics like data art, career advice, historical visualizations and more! I’ve used the community to ask questions about research and found out about a great data visualization exhibit at the Museum of the City of New York called “Who We Are”. There’s truly something for everyone looking to learn more about data viz!

Michael: I loved your article on Florence Nightingale and the Three Strengths of Polar Area Diagrams that you posted on LinkedIn. Can you briefly summarize it for my readers?

Allen: This article was one of my earlier installments and a great way to honor women’s History month while giving a quick shout out to PI day! Most people know Florence Nightingale for being a nurse but what they might not know is she leveraged data to create infographics to save the lives of many. She created a polar area diagram chart that showed British troops in the Crimean War were dying mostly from infectious diseases due to unsanitary conditions at the hospital they were being treated at. 

Besides being a role model for women in STEM, Nightingale’s work speaks to the power of data literacy and that data exists across every career field.

Another historical figure who I applaud for his data literacy is W.E.B. DuBois. A writer and civil rights activist known for his collection of essays, The Soul of Black Folks, he also pioneered the nation’s most sophisticated quantitative research on race and the Black population. DuBois along with a team of university students was able to show through 60 full color charts that the African American community had shown advancement in less than half a century following the abolition of slavery in the United States in 1863.  

Florence Nightingale Link:

W.E.B. DuBois Link:

Michael: What is your favorite chart type to use to tell your stories and why?

Allen: When it comes to chart types, I like to keep it old school with the line and column/bar charts. These are easily digestible by a broad audience and with the right annotations and highlights and use of color can tell a cohesive story. Line charts are good in depicting trends over time and bar charts show distribution over time very well. There will be time when there is a more complex topic that a scatter plot can be useful but my go to is the basics.

Michael: What is next on your “To Do” list? What can the Tableau and data visualization communities expect to see from you in the near future?

Allen: I’m wrapping up on a proposal to teach data literacy in under-served communities through data apprenticeships. This is a win win where companies can have a diverse data literate workforce and members of under-served communities can have pathways to a tech career. Would love to chat with those interested in learning more and weigh in on the topic! 

In addition, I’m also focused on letting others know that you do not have to be a data scientist to be data literate through my article series. Make sure to check those out as well!




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