Why I Hitched My Wagon to Tableau

Disclaimer: About five years ago I bet my career on Tableau. Further, I use a portion of the money I make using Tableau to buy Bar-B-Q; I like this arrangement and am biased towards Tableau.

Earlier this month, the Gartner Magic Quadrant for Business Intelligence and Analytics was released. This is one of the most cited and reputable sources for gauging the competitive landscape of the BI space, and as such, its release is always eagerly anticipated and highly publicized. For the fifth consecutive year, Tableau was named as a ‘Leader’ in the Magic Quadrant for their combination of ‘Completeness of Vision’ and ‘Ability to Execute’.

Being my visual analytics tool of choice, I would be lying if I said I don’t look forward to some objective, third-party love for Tableau. However, I had a realization that this type of validation is only valuable because it helps the perception of Tableau from outsiders. It helps me to cite Gartner when trying to spread the word about Tableau, but for me personally, the report only confirms relatively tiny aspects of what I already know. The real reason I champion Tableau is below.

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The Best Data Visualization Tip I Learned in Sixth Grade

This is the first in a series of data visualization tips I learned before I was a teenager. If you would like to receive future updates, subscribe for free.

As I think back on my career as a data visualization consultant, I realize many of the best lessons I apply in my work were learned as a student in grade school. Long before Tableau was invented or I had heard of data visualization, I was a kid with a bad part in in his hair (yes, I had hair) at John Diemer Elementary in Overland Park, Kansas (Go Eagles!).

One day in sixth grade, a teacher called me over for a reading test. ‘A reading test?’ I thought excitedly. I was going to crush this thing. I’ve been reading since Kindergarten… I totally had this. Did this lady even know how many free pizzas I had earned in the BOOK IT! program? She was in for a real treat.

As I masterfully read each and every word on the page laid before me, my confidence only continued to build. These words were for amateurs; she should have at least known her audience and tried something a little more challenging. I couldn’t wait to share the news of my great triumph with my friends and family once this was over with.

That’s when I learned one of my best data visualization tips.

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Data Visualization: The Stolen Art

Make no mistake about it, data visualization is an art form. I always enjoy sharing the anecdote that I have created literally hundreds of data visualizations, and to this day, not a single one of them has been perfect to everyone that saw it. There is always feedback, criticisms, and ideas about how to do it better.

That’s perfectly okay with me. It tells me the audience is engaged and that my work has the opportunity to start a conversation around data. When the feedback is constructive, sometimes I get a better idea about how to do something; other times there were explicit reasons for my choices and I politely deflect. I don’t take any of it personally because art is in the eye of the beholder, and data visualization is an art.

I imagine that’s what makes so many of us passionate about honing our craft. After all, not every job or practice makes you willingly want to practice on weekends and share your work with the world. For many of us, data visualization is our calling because it is the perfect balance between the left and right sides of our brain. With the proliferation of tools that are making the work of data visualization practitioners public, combined with those practitioners pushing to evolve their work, there is one trend I’ve seen that we need to collectively consider…

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3 Ways Psychological Schemas Can Improve Your Data Visualization

Whether you are aware of it or not, you are constantly recognizing and processing patterns in your everyday life. Think about when you go to dinner at a sit-down restaurant that you’ve never been to before. Even though you’re trying the restaurant for the first time, you will have some expectation about the order of events. This is one of many examples of a psychological schema (not to be confused with database schema) in your everyday life. These patterns help society align diverse audiences and help us process varying situations very efficiently.

Schemas play an important role in data visualization because they have the ability to make or break the two biggest benefits of visualizing data: reducing time to insight and improving the accuracy of insights. Tap into your audience’s schemas and you improve their experience; disrupt their schemas and you run the risk of leading your audience in the wrong direction.

This post shares three ways to leverage schemas to improve your data visualization.

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5 Lessons Learned While Becoming a Tableau Zen Master

This month I received the news that I had finally reached a career-long goal of being named a Tableau Zen Master – Tableau’s highest honor. As the outpouring of support was felt from the community, I put a lot of thought into the most appropriate response. I quickly realized that simply responding to tweets or LinkedIn messages would not do it justice, so I’m documenting some thoughts here to share with the community.

I’ve learned so much about myself and what it takes to find success with something during my 7-year journey, and I thought I should share some of those lessons in case somebody else can find value in them, get inspired, and/or overcome a dip in their own path.

Keep Pushing

I was really bad at Tableau when I started using it. I mean really bad.

I have an MBA and Master of Sport Business Management. My school education did not include a single day of code and I was not “raised” with a background in data. I went through the same struggles as a lot of new users, especially when trying to quickly transition existing Excel reports to Tableau.

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