Duplicating Datasources for Fun and Profit

Posted on Leave a commentPosted in Uncategorized

This short post was inspired by a Tableau Forum post forwarded to me by Wilson yesterday: https://community.tableau.com/thread/239017 To Summarize: I want to select a month in a time series view and use it to see that month in comparison to other months. This sounds simple but because of the way filter actions work it can be tough to achieve. Basically, a filter action restricts the target views to only the data contained in the selection you made – that means when we pick one month, we lose the context required to do month-over-month comparisons. There are some ways re-design the dashboard so it does what we want – We could require the user to select two months (by clicking-and-dragging or holding down the ctrl key). That works, but it could be a little confusing for our end user. Or, we could use quick filters or parameters to control the target view in a different way than by using filter actions. Clear directions on the dashboard would make this easy to use. But it might not be as delightful as clicking directly on the visualization. Finally, we could write an L.O.D. expression – the FIXED command operates before filters on the target view, meaning if we’re clever […]

The Hamburger Magic Quadrant, Introduction

Posted on Leave a commentPosted in Analytics, Hamburgers

“I could really go for a Hamburger right about now” It started on an evening in January. Strolling out of the office, Wilson and I look to each other and decide in the moment to trod not in the direction of the Union Square subway stop but down 5th avenue toward a restaurant we’ve heard serves the best burger we’ll ever try. The Art of the Hamburger Truthfully, that’s how all hamburgers start. The hamburger isn’t an “I’m gonna plan my night around this” type of food group. It’s something you get while sitting at a bar. Despite the trend of some restaurants toward offering a gourmand burger, the vast majority of hamburgers are consumed by people who look at each other and say “yeah, why not grab a burger?” I don’t need data to support that statement. I just know. I can also tell you as a long time purveyor of hamburgers that there are a disproportionate number of bars where, hanging in the corner, you’ll find a chalkboard where written in thick washable Crayola you’ll find the claim “Best Burger in Town.” And the great thing about these hamburgers is that they’re all, with small exception, the best burger in town […]

Podcast: The Tableau Journey with MK Quigley

Posted on Leave a commentPosted in Podcasts

“My job isn’t to change things to Times New Roman a thousand times” – MK Quigley Listen in brower: MK is a former coworker of mine, though before that she was a customer, and now she is a customer again. She is frighteningly smart and has the unique combination of creative thinking skills and logical reasoning that makes for a spectacular Tableau analyst. And despite that, she doesn’t refer to herself as an analyst. This episode was scheduled for an hour but we just kept talking. Things we discussed: Realizing, upon starting in an analyst role, that things you previously thought should be simple are actually incredibly complicated. The credibility that comes with admitting you don’t know something. Is “analyst” a job or a function? Features that we wish Tableau would build. Features that we hope Tableau doesn’t build – *ahem* – Dynamic Parameters, we’re coming for you. I’m so glad to have had a non-employee on. Hopefully we’ll have some more brave customers step up and brave the Thunderdome that is my kitchen table / podcast studio. Thanks for listening. Podcast notes: You can listen to Tableau on Tableau using any podcast app. Just search for Tableau on Tableau. Or, if you’re […]

Corr Studies

Posted on Leave a commentPosted in Calculation Lessons, Today I Learned

Tableau 10.2 came out a couple weeks ago and a small but notable feature included in this version of our product is the Corr() and Window_Corr() functions. These calculations compute a coefficient of correlation based on two variables. I’ve done linear algebra in Tableau before, and it’s often quite complicated and looks like this:   The idea with making Corr a simple function in Tableau is to give users a faster and simpler way to find statistical results. But I was confused. correlation coefficients operate on large groups of numbers, so why would it make sense to aggregate a pair of measures with Corr()? How would the aggregation change based on the layout of a Tableau worksheet? And how could I check the results to make sure I was seeing the correlation coefficient I wanted to see? When doing complex calculations, you often get a seemingly arbitrary number as a result, and some faith is required to trust that the number is answering the question you intended to ask, and not a different question. Below are some findings from my Corr studies: A quick preamble about my math background. I was always pretty good at math growing up, but I […]

Podcast: Gartner and Tableau 10.2

Posted on Leave a commentPosted in Podcasts

“I really believe that we need to make access to data so easy that it becomes an intrinsic part of conversation – I struggle to think about any organization that hasn’t quite gotten there.” – Wilson Listen in browser:   It’s been a while. Wilson and I have mixed feelings about the annual Gartner reports for B.I. and other enterprise technologies. On one hand, they serve as reliable independent documents that reflect a consultative view of various technical markets. They tend to be progressive enough to point out exciting new technologies and present a fair opinion of all of the companies they evaluate. On the other hand, they are primarily based on customer interviews – which aren’t always particularly progressive. It’s also difficult to tell how much they weigh things unrelated to technology, like company financial health or brand recognition. Their measurements, “ability to execute” and “completeness of vision,” are cryptic and warrant more explanation. This episode starts with a discussion of how we see the space. There’s a lot of focus on visualization, which is great, but it fails to focus on the differences between each technology. I wrote a bit more about this in a recent blog. I read […]

The Simplest Way and The Best Way: How Tableau Consultants Learn

Posted on 2 CommentsPosted in Calculation Lessons, Tableau Tips and Tricks

“You answered the question correctly, but you lost the sale.” I’m 26 years old and I’ve been working at Tableau for approximately 6 months. I’m on the phone with Marc Rueter who is dialing in from an undisclosed location (i.e. across the hall) in the Lakeview building, Fremont, Washington, the 4th floor of which houses the entirety of Tableau Software, Inc. presently in the summer of 2011. Those of us who worked at Tableau at this time, particularly the technical experts, consider Marc Rueter to be something of a god. He designed the Product Consultant role that was my entry-level job at the firm, and he defined the strategy behind all of Tableau’s training, pre-sales consulting, services delivery, and more as the company emerged as a startup. Marc interviewed me, hired me, mentored me, and now was proctoring my Gold Certification, the highest level of internal product certification Tableau offers. I had invested weeks into preparing for the technical questions he would ask, which started from a common list of prepared challenges but quickly spun into off-the-rails and improvised challenges designed to hurt your confidence and test your ability to adapt when dealing with a particularly difficult customer. Sometimes the […]

Data Radicalization

Posted on 1 CommentPosted in The Soapbox

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 […]

Makeover Monday: Not Saying “Groin”

Posted on Leave a commentPosted in Makeover Monday, Viz Review

Sometimes I take things too seriously. This week’s Makeover Monday is a great example. It comes from a fivethirtyeight article about how the sports media refers to male professional athletes getting kicked in the groin, referencing a particular example from this year’s NBA playoffs. After Steven Adams was unceremoniously jumbled in the porker by Draymond Green, hundreds of journalisms gleefully took to the internet to write about it. The article, written by Kyle Wagner, takes a lighthearted look at the differences between the styles used by various sports media outlets, noting the proliferation of the word “groin” and surprising avoidance of the word “penis.” Wagner suggests that this is of some concern, possibly implying that journalists avoid terms the public will react to in disgust especially in an internet-medium where traffic is king. I have a hard time leaving it at that. Outside of having fun using phrases like “jumbled in the porker,” what I see when I look at this data set is a study in the evolution of language. The viz in Wagner’s article is heavy in text and settles for telling the story that “Groin” is used more than other terms. It is largely a crosstab, useful […]

Makeover Monday: The Next to Die

Posted on Leave a commentPosted in Makeover Monday, Viz Review

Andy and Andy have been posting a series of relatively morbid Makeover Monday topics recently, perhaps none as somber as The Next to Die – an exploration of death penalty executions across the United States since 1976. It’s possible that this topic is on my mind because we’re currently in an incredible political season in America, but I’ve found myself thinking more and more lately about the concept of communicating facts and their importance when making a persuasive argument. “The Next to Die” repeatedly makes claims to its own impartiality, reflecting upon the lack of opinion it portrays about the morality or efficacy of the death penalty. However it is clearly a politically-driven document, and its motivations are transparent the second you read it. Any critique of the visualizations presented within “The Next to Die” must consider the intended argument and the language used in addition to the visual design of the pictures portrayed within. The Map This map is still difficult for me to understand. While i appreciate the effort to normalize the size of states to avoid the intrinsic bias in over-representing larger geographic areas, I find the use of color confusing. The brightness of the red coloring indicates […]

Makeover Monday – Breaking Convention to Capture Attention

Posted on Leave a commentPosted in Makeover Monday

In the most recent episode of Tableau on Tableau, Dustin Smith and I briefly mentioned what we refer to as the “Andy Cotgreave” method – which is reflected in a lot of the British Andy’s visualization work. I brought up Andy’s tendency to defy convention in the interest of making visuals which will start conversations and draw his audience in. There are pros and cons to this approach. On one hand, and as more comprehensively described by Robert Kosara, a data graphic designed purely for presentation purposes can be more memorable if it contains creative or pictographic elements. This can make an audience remember and care about your point even without a complete understanding of the data. Alternatively, breaking visual best-practices can distract from the real conversation if you’re in a room full of data viz experts, and it can create real barriers to entry for your audience. If they can’t quickly understand your view, it doesn’t matter how great it looks. Perhaps this topic is what made me take the approach I took for this weeks’ Makeover Monday exercise. First, take a look at the source viz, published on cnn.com. I looked at this viz and read the article, and these […]