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Data Literacy Is the Key to the Future of Data Visualization

A conversation with Data Literacy, LLC founder Ben Jones about the power of user stories and the urgent importance of teaching the language of data

Ben Jones is the CEO of Data Literacy, LLC. He’s on a mission to help people learn the language of data.

Ben Jones is the founder and CEO of Data Literacy, LLC, a training and education company that’s on a mission to help people learn the language of data. Ben is a highly experienced and passionate instructor, having taught data to thousands in a corporate training environment as well as in academic classroom settings at the University of Washington. Prior to starting Data Literacy, LLC, Ben worked at Tableau for six years in a range of roles from senior Tableau public product manager to technical evangelism director.

I met Ben Jones at a Tableau User Event about two and a half years ago. He was giving a keynote about Tableau Public and the growing influence of liberal arts in data analysis. He pointed out that a liberal arts perspective can improve the way our organizations make use of data because they possess a lot of the key skills needed for analysis such as critical thinking and context setting. He wanted the audience to know that the science of data analysis combined with a liberal arts perspective is becoming more powerful and effective than ever. I was captivated to hear and see how Tableau was being used outside of the traditional analytics and data science applications. Ben spoke passionately about the Tableau author’s dashboard creations like they were his close friends. You can tell he was proud of their work. I left the event feeling very inspired.

In the time since, Ben has left Tableau to start his own consultancy, Data Literacy, LLC. He helps his customers become more data literate through training that is online or on-site. Whether it is individual or customized team-based training, their aim is to demystify data and to make learning more enjoyable. Their mantra is that data simply provides a lens into our world and our humanity.

Fortunately, our paths have crossed again and I now have that same feeling of aspiration as we chat about where he sees the data visualization space going.

Allen Hillery: Tell me about your experience at Tableau and your role there?

Ben Jones: Tableau was and still is a wonderful company to work for. Great culture, amazing product, fanatical customers. I moved up to Seattle from Southern California to work on the Tableau Public platform in January 2013, about half a year before the company went public. It was an opportunity of a lifetime and such an enjoyable ride for me. Worldwide usage of the free platform grew 20X while I was there, and it felt like I was part of a movement more than anything. It was more than a job for me. I also got to lead the Academic Programs team, which afforded me the opportunity to work with instructors and students around the world to teach the next wave of professionals how to see and understand their data.

AH: What did you find motivating about your role?

BJ: There were three main things about the role that motivated me like no other role I had up to that point.

First, there was the impact we were having. People around the world started using Tableau’s free data-sharing platform to ignite these powerful data dialogues about really important topics like heart disease, gender parity, and gay marriage. From journalists in Buenos Aires exposing government corruption to oceanographers in San Diego tracking manta ray populations in Baja California. Heady stuff.

Second, there was an explosion of creativity. Data nerds in all industries flocked to the platform to work on “passion projects” that were completely free of stifling constraints imposed by corporate overlords. This resulted in so much expression and innovation. People may not remember, but not too long ago, it was very taboo to incorporate artistic elements (a.k.a chartjunk) into data visualizations. Tableau Public was part of the reason the pendulum swung away from that.

Third, there was the professional growth experienced by users of the platform. When you run a contest that someone wins, and then they get hired by an amazing company in New York and their salary more than doubles, you get the satisfaction of knowing that you played a small role in their journey. That’s very gratifying.

AH: It sounds like you encountered a lot of data stories! Tell me about your most inspiring user story that personally impacted you.

BJ: Oh there are so many inspiring Tableau Public stories. I guess a few come readily to mind. I’ll never forget the story of Sarah Ryley on NY Daily News working all night in the aftermath of Eric Garner’s death to uncover racial disparities in the NYPD’s “broken windows” policy. She went on to win a Pulitzer Prize for that work.

Sarah Ryley produced these Tableau Public dashboards to show the racial disparities of summonses issued since the introduction of the NYPD’s “Broken Windows” policing in NYC. Broken windows is a criminological theory that states the visible signs of crime will encourage further crime. On the right, she highlights police stops where force was used. The color-coding shows the type of force used.

And then there’s the whole multi-year journey of the data journalism team at La Nación to continue exposing government corruption in Argentina in spite of the government pulling advertising from the paper. These individuals are strong and courageous and I felt honored to support them.

In August 2018, Argentina’s leading newspaper, La Nación, published an explosive report on public corruption. Argentina has long suffered from high levels of corruption, which has plagued the country under all political parties and economic models. Their Tableau dashboard above graphs Argentina’s risk score against presidential administrations.

But there’s another story, and I won’t share the name of the user or even really the story, because it’s theirs, not mine. A very talented Tableau Public author reached out to me and described their childhood of extreme poverty, and their tenacity to rise above it using education and data literacy and leveraging everything they could just be made me sit there and cry. Maybe one day that person will tell that story.

AH: From the time you started with Tableau until you left, what changes did you observe in the type of users, the stories being told, etc.

Tableau dashboard showing property rentals in Minsk.

BJ: Interesting question. The look and feel of what was being created changed more than anything else, I’d say. We were teaching each other new techniques, the software was evolving, and the overall DataViz space was undergoing a massive innovation wave. The movement jumped from primarily a US-based thing to a global thing fairly early in my time at Tableau, so I started seeing stories about property rentals in Minsk and changes in Congress in Peru. That never stopped. Over two-thirds of the views of Tableau Public came from outside the US and Canada, so it was the most international aspect of Tableau for some time.

Tableau dashboard author, Angel Hugo Pilares of Peru’s El Comercio shows the political party-line breakdown of the Peruvian senate. Angel uses a unique graphical representation of the actual layout of the senate chamber to bring his data to life.

AH: How fulfilling did you find it to watch someone go from novice to power user? How would you gauge user’s data literacy?

BJ: That was a lot of fun for me! I got hooked on it, actually. While I was working at Tableau, I was also teaching at the University of Washington’s Continuum College (I still am). And when you’re part of someone’s light bulb/eureka moment, there’s no going back. This is the main reason I left Tableau to do what I’m doing now at Data Literacy.

AH: Can you elaborate more on what motivated your move from Tableau to starting up Data Literacy, LLC?

BJ: Toward the end of my time at Tableau, I started to hear something over and over again. In so many conversations I had with people in corporations of all industries I started to hear about a massive education gap that exists in our era. “It’s great,” they would say, “that we can make a histogram with these awesome tools, and that amazing videos and tutorials exist to help us know how to do that. But the people in our company don’t know how to read one. They don’t know what it means.”

I lost track of how many times I had a variation of that conversation with someone. This capability gap lines up perfectly with my passion to help people get to that light bulb moment with data. I had always wanted to start and run a business, so I got to the point where I felt I had no choice. I couldn’t get to 80 or 85 and look back and wonder what would have happened. So now I’m finding out!

AH: What do you aspire to achieve with Data Literacy, LLC ?

BJ: I hope to help people speak the language of data. I want to build confidence in “data-phobic” people to better read and interpret charts and graphs and dashboards, and I want to help people develop useful data-working skills to tackle new challenges in their careers and in our societies.

AH: It sounds like you’re already doing that with a new book coming soon?

BJ: Yes! It’s titled Avoiding Data Pitfalls. It’s been in the works for a while now but the good part of this journey is that I had the chance to make many more mistakes with data, and I was sure to incorporate warnings about those pitfalls into the book.

AH: The title alone piques my interest! How much of an impact are you expecting it to make on readers?

BJ: I wrote this book so that if time travel ever becomes a thing, I can go back in time and give it to an earlier version of me, along with some killer stock tips, and a stern note about a Peruvian restaurant in Vancouver to avoid. Obviously, that hasn’t happened, and likely won’t but I’m hoping this book can be helpful for others embarking on the journey of data exploration, and even perhaps those already on the journey, who, like me have the bumps and bruises from the pitfalls to prove it.

AH: How important is data literacy in your opinion?

BJ: I believe advancing data literacy can be one of the most important contributions of our generation and the next few generations to come. It’s a relatively new language for us if you look at the big picture.

Anatomically modern humans first appear in the fossil record around 195,000 years ago in Africa, but Alan Turing set out the idea of the modern computer in his seminal 1936 paper, only 80 years ago. That means we’ve been acclimating to the computing era for a grand total of 0.04 percent of human history. That’s a fraction of a day that occurs in the last 35 seconds, between 11:59:25 pm and 12:00:00 am.

So our generation has the critical job of the data infant for our species. Learning to crawl and then walk but figuring out how to put data to use. Building an immune system that defends us against costly data blunders. Who else is going to do this for our species?

AH: Where do you see the data viz space going? Do you see the same passion and hunger from users?

BJ: Yes, I really don’t see anything abating, to be honest. It has grown so much, and there are so many new voices and contributions being made every month that goes by. I hope to see three major changes take place in the coming years.

First, I hope to see more diversity of voices. Dataviz is part of STEM, and subject to the same biases and inertia, but I believe DataViz can take a leadership role in STEM and help point the way to a more inclusive world. I’m encouraged by conversations happening right now, and I’m optimistic that we can carve out a path forward.

Second, I’d like to see bridges formed across tool-based silos in DataViz. There’s no reason to be exclusively based on your tool of choice. There will always be subgroups that help each other learn specific skills, and that’s great, but there need to be more connections at the higher level of concepts and ideas.

Third, DataViz is still very niche. It’s so much larger than it used to be before tools like Tableau and Power BI opened the doors for many others to join, but there are still so many people on the outside who don’t see data and visualization as something that they’re a part of.

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