Data literacy, moving beyond visualization, and the cultural impact of the Tableau mission
Note: I work for Tableau, but the comments in this article and through the rest of this site are my own. I think these ideas are true, and smart, and right. But they do not necessarily represent the views of Tableau.
Tableau has been successful at convincing people that the problem with data analysis is a traditional lack of visualization. Visualization makes data more accessible for everyone and drives engagement with information.
Looking at our website, promotional materials, and branding, this is apparent. Go to tableau.com and you’ll be instantly confronted with bright, colorful visualizations on a myriad of devices, active verbs like “inspire” and “impact” and “drive” and pictures of smiling people delighted by what they’ve found in their data.
This is all great. I’m not complaining. We’ve moved an entire industry centered around high priests acting as data gatekeepers and accumulating information like oil without ever getting value from it. We’ve forced this section of society to consider the everyman. I think Tableau, as a company, should take credit for the massive shift in a market worth tens of billions of dollars and be proud that technology megabehemoths like Microsoft and SAP are adopting our terminology and sales models, if not our vision.
But in focusing on visualization as the key to data analysis, we have hamstrung ourselves in a couple of ways. Firstly, we’ve championed designers and visual artists as representatives of the magical impact one can make with data. The Tableau Zen Master program* is a great example of this. It’s a fantastic program and has turned some of our most passionate customers and partners into minor celebrities. The problem is that it has substituted a new type of specialization for the development skills our messaging decries.
*The intention of the Tableau Zen Master program is not specifically to celebrate visual designers. But as a result of Tableau’s marketing campaigns, promotional materials and conferences, and in response to the type of people who have become most passionate about our products, we have historically recognized people who specialize in design and can create beautiful data visualizations, rather than others who might be more technical or specialize in other important areas surrounding data.
Visual designers tend not to be as technically savvy as the I.T. personnel who build reports in traditional B.I. methodologies, but they are still specialists. They have degrees and accreditations founded in scientific research and years of study. If businesses are convinced that visualization is the key to getting value out of the massive amounts of data they produce and collect, then a piece of software that makes visualization easier doesn’t help them as much as employing specialists who are skilled enough to build beautiful pictures of their data.
In this paradigm, Tableau as a software is unimportant and “visualization” as a skill set is crucial. But these visual artists are trained in many different skills including the use of competing products (Qlik, Microstrategy) and open-source or free libraries (D3, Google Charts) or other specialist softwares (Adobe Illustrator) used to practice their art. Because as Alberto Cairo proves in his excellent book, A Functional Art, data visualization may have utility, but it is indeed an art with aesthetic principles based on the functional value they provide. Not unlike architecture, it is a trade that requires extensive training in both technical and aesthetic areas.
This is the problem: Creating a visualization for people to read and interpret may help improve the story behind a set of data, but it can only communicate stories that exist within the worldviews and assumptions of the creators.
Data analysis should accelerate and amplify knowledge, and that knowledge should help people make better decisions. People are best informed when they can ask their own questions and make their own decisions, and quite importantly understand why they are making those decisions. It doesn’t hurt to have advisors who understand the issues to help you stay informed, but you can’t offload all of the knowledge to specialists. It is inefficient, expensive, and prohibits people from pursuing their own ideas.
The second problem created by championing visualization is that it has created a commodity. Competitors (the aforementioned Microsoft and QlikTech, most notably) have take note of the excitement consumers have for data visualization and the impact Tableau has had on the market, and they have replicated the approach and communication that has made Tableau successful. That’s why their products look an awful lot like Tableau – because visualization is a commodity as well as an art – its principles and best practices are available to the world at large, already, for free, and people who choose to pay for it do so for productivity and efficiency reasons rather than to transform their businesses.
The thing is, Tableau’s vision is transformative.
In a mature market, building products purely in response to customer need is a correct approach. If customers want tools to create data visualizations, companies should create them and sell them. The best, most cost-effective ones will succeed. That’s the foundation of our economy.
But data analysis is immature. We see it every day. In sports, in politics, in business, and in our personal lives. Decisions are made by gut feelings and emotions rather than by fully informed people who feel that they understand all of the implications of their decisions. There is nothing wrong with trusting your gut, but your gut will be more successful when it is a fully informed gut.
That’s why the market needs products that are accessible for everybody, business people, non-profit workers, educators and students, congressmen and constituents. And that’s why the market needs experts (these aforementioned specialists) to teach these everybodies to fish by explaining why and how they can become data-literate.
Visualization is an avenue for understanding. It does not equate to understanding. It does not replace the general familiarity with basic mathematics and structures surrounding data that are necessary for people to make informed, competent decisions based on facts. This general familiarity should be a requirement of every worker in our society and should be taught at an elementary school level. An informed public can make reasonable decisions and reject false information or distractions when it will detract from their lives. And there is nothing more crucial to being informed than data.
That’s why I work at Tableau.
I see Tableau’s mission, “Helping People See and Understand Data,” as a progressive and revolutionary one. And I see the other companies who sell competing products and attempt the marginalize our market share in order to retain the maintenance fees on their own legacy products as comparable to politicians who spew “alternative facts” in order to confuse and distract the public.
Tableau’s customers are at varying stages of data maturity, but the vision as I interpret it is to create a society where people are encouraged to ask questions, pursue ideas, and present facts as evidence when they want to advance their own ideas and agendas. The people who will be helped by this pursuit deserve more than beautiful pictures. They deserve the simplicity, sophistication, and education to engage in these questions themselves.
I’ve been away from this website for a while, working, thinking and deciding how I can make an impact and advance this vision. But this is my new thing.