Dustin introduced me to Tableau. I was 24, and I was working at a small tech startup in Seattle. I had just gotten a promotion to the title of “Junior Business Analyst.” I’m still not sure what that means. Dustin and I were tasked with manipulating data, all day, and delivering it to people in the business and sometimes to our customers. One day Dustin turned to me and said, “You know, why don’t you try messing around with this Tableau thing?” I downloaded a free trial and opened up Tableau version 4.1. I went to the website and listened to the training video, recorded by Marc Rueter. At one point I swiveled around in my chair and said to Dustin, “This is pretty fucking cool.” A year later we were both working at Tableau. There are a lot of funny stories that emerge at people’s jobs. Our stories happen to be about data. We are curious about everything, and if there’s data on it, we want to analyze it. These may just sound like funny stories, but they are pivotal to how we developed as employees, as professionals, and as people. They shaped our careers, and the growth of Tableau […]
I have a new employee! As many of you may know I manage a small team of technical pre-sales consultants at Tableau and one of my challenges is finding a way to train / “ramp-up” new people. Tableau has numerous resources to teach our new hires the methodologies and technical skills relevant to their job experience, and we even send every new hire to Seattle to spend 2 weeks meeting their coworkers, getting ingrained in the culture, and understanding our history and our mission. But one area where we haven’t invested as much as I think we should is in teaching visualization skills. Odd for a data visualization company, right? Well, there are a lot of things you have to know about when you’re a Tableau technical expert. Server implementation techniques. Analytical math. Hardware sizing and scoping. Being able to create a beautiful viz is understandably lower on the list, especially when you consider the fact that businesses usually have their own requirements for data viz design and they aren’t always in line with design best practice. But I think being able to create competent data-oriented stories is an important skill to have for any technical consultant, and in our […]
After a bit of a hiatus, I decided to try my hand at another of Andy and Andy’s Makeover Monday challenges. This week’s view comes from UK business insider. The headline: American women work way more than their European counterparts. I think the problem with this viz isn’t the chart type. A stacked bar is actually a fine way to represent distribution for a data set like this one which buckets “hours worked” into 5 categories. You can clearly see that the percentage of people who work more than 40 hours are higher in the US versus the other countries shown, and higher than the average. But here lies the problem: not very many countries are shown! The author handpicks Japan, France, Germany, Italy, and the UK as countries for comparison, but I see no reason why those countries should be a representative sample of all of Europe, as the title of the article indicates. As a journalist, I think it’s one’s responsibility to make sure that your claims are backed by data, and not just the part of the data that you think supports your argument. When I looked at the data I saw something different. Sure, there were […]
At our company meeting in Seattle, the four Viz Wiz finalists met to present their final data visualizations in front of an audience of over a thousand. It was a great even and Wilson and I always love seeing how excited people at Tableau are about the skills and expertise made possible by our technology. Here’s a brief overview of the entries with a few comments on each (click each name to open the viz in a new window). Tony Kao Tony did a very thorough analysis of the data set. I think his first viz is fantastic – something I haven’t seen before that really tells a story. Could fit right into an article about gender representation in film. The rest of the views are analytical and deep. If there’s a flaw in this presentation is that it loses cohesiveness. I’m still learning about the best use of Story Points, but I find that they work best when there are only a few different visualizations where the pagination can point out progress or discrepancies between the views, and not as well when each visualization adds a new point. Simply leaving one viz and navigating to another causes me to […]
On an April 11th Podcast, Wilson and I talked about Andy Cotgreave’s Computerworld article about data visualization criticism. Since then, that article has become a bit of a hot button in the data viz community. I’ll not recap the entire argument here but if you’re interested you can visit Andy’s article which contains comments from Randy Olson and Stephen Few, and links to the original Wall Street Journal visualization as well as Randy’s critique of the viz. I mention this debate merely as a lead-in to my own data viz debate which occurred last week at Tableau’s annual All-Hands meeting in Seattle. There, Andy taught a class about analyzing Time Series data, in which he explored many different techniques for visualizing information that has to do with time. The generally accepted best practice for time series data is of course line chart, but Andy also discussed other techniques including the highlight-table approach linked in the article above. At the end of the class he called for a bit of a competition. Andy shared a data set with the class and asked everyone to build their best time-series view. Well, you all know how much I love competitions. I built the […]
Back by popular demand, Andrew Hill joins the podcast with Tableau employee Dan Huff and special guests Matt Higgins and Scott Wasserman to discuss the things companies often fail to consider when implementing Tableau. Analytics success is tied to software, leadership, and people. Also, Andrew gets a surprise.
Wilson and I have learned a lot this year from operating the Viz Wiz tournament (“Wiz” now officially branded by CMO Elissa Fink as sans-h), which isn’t the first visualization tournament we’ve run at Tableau, but it’s by far the biggest. Next week we’ll crown a champion. For now, listen to our shock-jock analysis of the bracket, the judges, and the competitors left in this year’s tournament. The topic of visual artistry and the decisions made when designing a data viz is muddled with trying to balance the visual best practices, decreed by Edward Tufte and evangelized by new business-focused data scientists like Stephen Few, with design principles long associated with graphics in journalism and other visual mediums. When Andy Cotgreave was on the program a few months ago, he mentioned “Cotgreave’s Law,” which teases that more innovative data visualizations inevitably create more criticism. A recent article Andy published on the topic can be found here. To illustrate this topic, and two of my favorite visual practices – the highlight table and the linear story layout, enjoy an entry from one of the Viz Wiz tournament finalists, Team “Extreme Viz-Over” – the partnership of Rafi Zelikowsky and Luca Bandini. Here’s […]
The cocktail scene has gotten out of control. I can go to a bar in Manhattan and spend $20 on a drink. I guess I’m paying for the ambience or service or decor at a fancy bar or maybe I’m paying for the fact that it’s “crafted” for me by a guy wearing suspenders because remember when people wore suspenders? Me either. Anyway this episode is about Self Service Analytics. If you want to subscribe to the podcast, you can do so on iTunes or on Stitcher.
What rolls down stairs Alone or in pairs, Rolls over your neighbor’s dog? What’s great for a snack And fits on your back? It’s log, log, log! I’m known for tenuous analogies, so I won’t spend too much time defending the connection between the classic song from TV’s Ren & Stimpy and the logarithmic axis on charts. Except to say this: like a heavy log, this brute force tool is rarely the appropriate weapon of choice for representing a numeric range. A couple of weeks ago, Andy Cotgreave explored the notion of a logarithmic axis on one of his Makeover Monday vizzes. In this case he was attempting to deal with the vast difference between soccer (née “football”) salaries between the highest English league and other, lower divisions. His attempt (click to read his original article): As Andy notes in his post, the logarithmic scale doesn’t fix the problem of range in this view: The default scale slope (on the left) makes all the lines appear as if they start from the same point. I tried a log scale which fixes it, but I think log scales are misleading for many viewers, who either don’t understand what they show, […]
In my last article we talked about aggregation. This is the most important principle of calculations in Tableau. As you’ll see, aggregation affects every other concept in calculations. Want to understand Table Calculations or LODs? You’d better damn well understand how Tableau aggregates data. But those are topics for a future post. You aren’t ready. Today we’re going to discuss logic and how it impacts calculations in Tableau. What Does Logic Mean When You’re Writing Calculations? “Logic” is a very abstract, nebulous term. I am being intentionally vague right now. We are not going to cover the difficult, theoretical concept of logic that you may have taken a course on during the process of obtaining your liberal arts degree. Though as a holder of a liberal arts degree myself the concept is intriguing. We are going to talk about using logic as part of your calculations in Tableau. And I know you will be surprised to hear this but logic in Tableau has a great deal to do with aggregation. Crack open the Tableau calculated field dialog box and filter the syntax to “Logical” and you’ll see this: This window is full of logical operators like “If” “And” and “Then” […]