Q: Being an independent consultant can be challenging. And, being a woman in tech presents different kinds of challenges. Do you feel any discrimination exists against women in tech?

Martin: “Tech” has a vision problem, as in there’s a real danger of being myopic and losing its ability to be creative and adaptive. A good example of this is how Microsoft became a big, bland, slow, monolith (I only mention Microsoft because I’ve read that they are trying to change this). How do you “think outside of the box” if you’re sitting in the box talking to a mirror? I understand that it seems easier to communicate, and you know that everyone in the box will love your ideas, but diversity – whether it be age, culture or sex – is healthier, more productive and more innovative in the long run. If you only let the monkeys build the zoo, you will have a zoo that only monkeys could love.

Being an independent consultant is much, much easier. I don’t get contacted by people who have those biases. I also think that my focus on Tableau consulting has a lot to do with it. Tableau isn’t being used by just the “tech” folk in most organizations, it’s being loved by the analysts and management in all departments. There are way more analysts in most organizations than are in IT or BI, and those departments don’t have as much of a diversity problem (e.g. finance, marketing, sales, operations). That’s why you see so much more diversity (with the exception of race) at Tableau’s annual conference.

Q: How would you describe your dashboard design approach? Pragmatic? Artistic? Both?

Martin: I like Stephen Few’s definition of data sensemaking. So, by that measure, I guess I’m pragmatic. But that doesn’t mean a step-by-step approach.

I tend to learn what I need to, then just go and do fast without thinking about it much. Do the homework, make a huge mess and clean it up with a critical eye. Is that both or creative? Or nuts?

Q: How do you approach discovery work with Tableau?

Martin: It’s a combination of research, frameworks and curiosity. Initially, I have to understand the measures and their context, which means I may have to do some research. Because my background is in planning and evaluation, I tend to approach a lot of the investigation through that framework (inputs > outputs > outcomes). But first, I will go through all the fields, checking frequencies, descriptives and relationships.

I love using Tableau for discovery. It’s addictive. Before Tableau, this part was so onerous and quite subjective. You were basically testing a bunch of hypotheses that could be very time consuming and often, we’d end up with “analysis paralysis” and squirrelly eyeballs. With Tableau, you can ask a lot of questions of your data – fast. One of my favorite games is to make a basic view and then hit all the Show Me charts rapidly until I run out of options. It’s amazing how many surprises I’ve had – it’s a random treasure hunt.

Q: What are some of your favorite dashboard designs that you’ve seen in the community? Why are they your favorites?

Martin: Are you kidding? We’re talking hundreds now. Here’s a few that stick out in my mind at the moment.

• Jeffrey Shaffer’s Music Major Data Minor – such a beautiful, enjoyable story of Jeffrey. Many items can be overwhelming, but this drew me in, and the Sankey was a beautiful surprise.
• Jim Wahl’s Small Multiple Masterpiece – so simple, clear and beautiful. This chart has solved many problems I’ve had of showing a lot of data and information in a way that can be absorbed in business.
• Steven Carter’s Adoption Gap – very simple, beautiful. I instantly knew what I was seeing and was delighted.
• Adam McCann’s Life Expectancy – a very different way of presenting this information but very effective. The overall dashboard composition is light and pleasing. Also, it inspired Nelson Davis’s Genocide and War Story Points viz – brilliant!
• George Gorczynski’s Morally Acceptable – I’m usually annoyed by radar charts, but this is wonderful.
• Matt Franis’ EPL Injuries – I often zone out when the subject of sports appears, but I couldn’t help myself – I clicked, I learned and thoroughly enjoyed this viz!

Q: What advice would you give to a person that wants to work full-time doing dashboard design?

Martin: In tech and BI, dashboards are considered to be the “sexy” part of the work because the finished product is what will excite the people receiving them. In traditional BI, the dashboard/report was the final step in a 10-12 step process. A developer would be tasked with carrying out the committee-agreed-upon requirements and design after multiple mock-ups were reviewed and approved.

With Tableau, I tend to think that there are only two steps: data wrangling and data analysis (or sensemaking). Building the dashboard is a component of data analysis. Making meaning from all the data and being able to communicate it effectively is more than knowing what colors, fonts, lines or white space to use. A full-time job doing dashboard design is a data analyst position.

So, I guess I would ask: “What kind of data analyst do you want to be?” In business, I’d suggest that they learn something of program evaluation (or Results Based Management, or Strategic Planning, or whatever the kids are calling it these days), as it helps you put a framework together to figure out what questions you should be asking of the data. I’m talking about certain businesses here. The 5W’s works well for web work (dashboards that are for public consumption and have a very specific, finite focus) and some projects, but sometimes it’s not enough. I’d also suggest you learn something of research methods, statistics and relational data (SQL).

But – and this is a big BUT – don’t let that scare you or slow you down! If you have a hankerin’ for dashboard design, then jump in – the water is fine. Download Tableau Public and find some data that interests you and start playing. Don’t judge, just follow your curiosity. That will drive you to learn the things you need as you go along. Connect with the Tableau community and you will find all the help and encouragement you can imagine.