Working at Tableau Software - A New Employee's Perspective

When I started in Tableau's marketing department two months ago, I wasn't sure what to expect. The largest company I'd worked for had fifteen employees and the smallest had one (myself). I loved working in the unpredictable environment of a fledgling company, where something was always on fire and agility was valued over planning. But I began to feel like I was stagnating – I was working hard, but my efforts were unfocused. I felt like I was reinventing the wheel and knew I needed to be someplace where I could learn from people with more experience.

It took me a few tries to find the right position. Less than three years ago, I was still working towards a Ph.D. in electrical engineering from UC Berkeley. Leaving the program was one of the hardest decisions I've made. I still remember standing calling my mother from the courtyard outside my office, trying to explain to her why I was walking away from all the time I'd invested.

My final internship had been the turning point. The work was interesting, but it didn't satisfy me. There wasn't anyone in my office that I could look at and think, "That's who I want to be thirty years down the road." As it happened, the people who did make me think that were all entrepreneurs, and so I left my Ph.D. to find a smaller company where I could get a taste of the non-technical world.

I found an early-stage startup delivering workshops on interpersonal communication and signed on as an unpaid intern. With barely ten employees, the company hierarchy was fairly flat, but I was at the absolute bottom, taking out trash and ordering pizza simply for the privilege of getting my foot in the door.

Fast forward eighteen months and I found myself teaching on three different continents and heading the European instructor team. My resulting career in public speaking opened the door to the world of online marketing, which was the perfect way to blend my technical background with my interests in business. Then I found Tableau. The chance to drive a website optimization project on a grand scale while simultaneously playing with gorgeous data visualizations was an opportunity I couldn't pass up.

During my interview, I was asked what would be most difficult for me as I transitioned to an office environment. I guessed that it would be dealing with red tape for the first time, but I couldn't have been more wrong. The lack of red tape and the individual empowerment here at Tableau has been breathtaking. From my first day, I've felt fully responsible for prioritizing my time – which means, in short, that I spend every minute of every day working on something that I personally believe is truly important to Tableau's success.

(For those still wondering, it turns out it's waking up on time that's been the biggest challenge. I'm getting better at it, little by little.)

[UPDATE] I recently posted the first visualization I made here at Tableau, an analysis of our keyword strategy for search engine optimization. Check it out!

DOT Car Seat Ratings: We Viz the Best Models

With the most recent DOT/NHTSA car seat ease of use data posted on data.gov, we created this viz to help parents choose a car seat that they can actually operate!

Choosing a car seat can be nerve-racking and confusing... likewise for using one. Use this viz to select your seat type and browse through each seat. As you can see, The First Years offerings seem to be leading the pack in ease of use.

Visually, this graphic is uncomplicated. We used stars, a symbol mentally associated with car safety, to enable quick browsing and consumer decision making. When making a viz that answers a simple question (which car seat is the easiest to use and why?), try to make it simple and intuitive by avoiding gimmicks and clutter.

Hanging Out With the Cool Kids

At heart, Tableau people are vizgeeks who get jazzed about telling stories with beautiful graphs. But the folks at High Moon Studios are game developers, and they’re cool. High Moon developed the Bourne Conspiracy game, and they’re working on a new top-secret game.

Game developers have to be smart as well as cool. Sean Houghton, the Technical Director of High Moon Studios, used Tableau to analyze consumption of the new game’s memory budget. He blogged it in Mungo Smash.

My favorite part of Sean’s analysis is the chart that shows that the Elevator Shaft consumes more memory than the Boiler Room. That’s somehow more exciting than finding that the East Region tends to be less profitable than West when selling new products. And I also learned that Weapons aren’t the big memory hogs—Characters are. That introduces an odd bit of data in the ongoing debate on the social utility of violent video games. Maybe they’re really character development games, and the characters just happen to have weapons.

Sean’s data analysis should be useful to any software developers who have to watch memory closely. And his post made us feel pretty good too: High Moon likes us.

PAHO Visualizes Haiti's Earthquakes

The Pan American Health Organization published an interactive dashboard showing the location of last week’s devastating earthquakes in Haiti. The view spans three days and makes it easy to see the sheer number and strength of the aftershocks that reached magnitude 5.9.

The huge 7.0 earthquake occurred about 15 miles from Port-Au-Prince (pop. > 1 million) while most of the strong aftershocks occurred further west near Petit-Goave (pop. 15K), perhaps saving 1000s of lives. The dashboard can be viewed on PAHO's website.

[EDIT] This visualization was made with the Tableau Public beta. The downloadable workbook does not work in any current version of Tableau (except 5.1 beta). To the best of my knowledge we're planning to release 5.1 sometime in February.

Graffiti in New York City

As part of our month long look into government data, we have created a viz that examines graffiti data posted by New York City on their Data Mine. The differences between boroughs is striking: Brooklyn has more graffiti incidents than Queens and Manhattan put together.

Looking at the boroughs by precinct across The Big Apple, one can quickly see that there are some differences in how graffiti is handled. For instance, Staten Island has very little graffiti, but the graffiti they do have lingers without cleanup for almost twice the citywide average. On the other side of the spectrum, Manhattan has over 2000 incidents of graffiti, but it is cleaned up in less than 17 days on average.