#DataDiscussions with Mike Cisneros

For the first week of #DataDiscussions we had the honour to host Tableau Zen Master Mike Cisneros.

Mike Cisneros is a data visualization professional and enthusiast, with more than 20 years' experience providing elegant, persuasive, and effective products to clients in the private and public sectors.

You can find out more about Mike’s amazing work at his personal blog mikevizneros.com

Mike’s views are always interesting and inspiring, so without further ado let’s dive into his answers:

 

Question 1 - What is your job? How do you use Tableau as part of it?

For the past six years or so, I’ve been a data analyst specifically in charge of data visualization for Evince Analytics, a small contracting company in the Washington D.C. area. Most of our clients are associated with the government in some capacity or another, which is not a sector renowned for its rapid adoption of new technologies. This often means that we are not able to convince everyone in the byzantine acquisitions chain to buy into our more sophisticated capabilities. It hurts my heart a little every time I offer to deliver an interactive, self-service analytics solution to the customer, only to get word back that what they REALLY want are some PDFs and PowerPoints, along with the raw data files.

Nevertheless, the speed and complexity of the analyses that we are able to perform with Tableau tend to elicit very positive responses—even if our clients, for whatever reason, don’t seem to want the capability to generate these same analyses on their own. Fortunately, this attitude does seem to be changing, at least in a few pockets of our clientele; I’m sure that once the first few dominoes start to fall it will only be a matter of time before “Can you just print it out for me” becomes a distant memory.

 

Question 2 - If you could give one piece of advice to a new Tableau starter what would it be?

There are a lot of reasons that could lead to someone getting started with Tableau. It could be that their company expects them to get familiar with it, because that’s what they use internally; it could be that a person is an analyst who’s tired of other BI tools, or who just wants to experiment with something a little more interactive than Excel; or it could be that a person is just a hobbyist who wants to get into data exploration and visualization, but isn’t ready to go crazy with custom coding yet. In all of these cases, though, the person will soon discover that it is quicker and easier to create a wide variety of charts and dashboards than they would have realized.

The time from “I know nothing about this tool” to “I just made a really cool looking dashboard” is short with Tableau. But the accelerated speed of creation, especially for newcomers to the tool, is a dangerous thing. When you can create rapidly and easily, it’s easy to get caught up in the excitement of your newfound abilities, and forget to ask yourself questions like: Is the data I’m working from reliable? Do I know where it came from? Are the charts I’m making representing the data accurately? Are all these filters I’m adding really necessary, or am I adding them in just because it’s so easy to do in Tableau? Am I picking optimal charts for my intended audience? Do I really understand the aggregations and calculations that Tableau is doing for me? Am I sure the math is doing what I think it’s doing?

So my advice to the new Tableau starter is: You’ve been handed an extraordinary tool that is powerful and easy to use. It’s important that you simultaneously study the craft that tool enables, and respect the materials you’ll use that tool upon.

 

 

Question 3 - If you could add a new feature to Tableau, what would it be?

So, although I’ve been a web developer, an editor, a community manager, and a data analyst at various times in my career, more than anything else I would say that I approach Tableau from the perspective of a designer. And because of that, it’s hard for me to pick one specific feature that I yearn for over all others; but speaking generally, I would love for Tableau to have the same kind of drawing and layout toolkits that we’ve grown accustomed to in other applications. And by “other applications,” I don’t mean Photoshop or Illustrator (although, that would be amazing). I mean, even the level of drawing and layout tools available in PowerPoint would be a quantum leap.

I’d like the ability to align and distribute elements. I’d like to draw shapes, to set transparencies, to rotate objects; I’d like to mask objects, to have vector-based graphics. (I’d also like a better labeling engine, so that we have options beyond “don’t show all the labels” or “show the labels stacked up on top of each other.”) None of these features are core to the mission of getting data cleaned, loaded into the software, and analyzed; but they are indispensable for presenting your final dashboards, reports, or charts to a customer in a unique, professional style--especially if they want products that mimic their existing branding.

For an analyst sitting at a computer using Tableau for her own purposes, just looking for answers to her own questions, finely-detailed formatting options aren’t critical. For me, a design-centered analyst who wants to sell more and more people on the beauty and elegance of the software, having this kind of control over the “fit and finish” of the products is a big deal.

 

Question 4 - What’s the best data book you’ve read recently?

The one I’m partway through and would recommend to anyone in the data analysis field, or in the field of being a human alive in the world right now, is “Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech” by Sara Wachter-Boettcher. It looks at the assumptions and unintended consequences that derive from those assumptions in our increasingly algorithm-shaped world.

On the graphic arts side of things, I’d pass on a recommendation that I got from Brit Cava and enjoyed: “Picture This: How Pictures Work” by Molly Bang. It’s not a new book by any means but it’s a good intro to color, shape, composition, and balance for anyone who wants to get started thinking about upping their visual skills. It’s short and simple and super accessible.

 

 

Question 5 - Do you have a data goal for this year?

I do, but it’s not one that I have a great sense of how to accomplish quite yet. I’ve seen a lot of great work done by people in this community, work that addresses social issues, political issues, human issues, global issues. Some of this work gets seen in the Tableau community writ large, either by virtue of being selected as a Viz of the Day or featured by Tableau in their social media communications. Sometimes, they’ll even get picked up by other outlets somehow. Adam Crahen and Pooja Gandhi’s Frostbite chart got a wider circulation that way. And of course, there are the IIB awards every year, but while that’s a big deal in our world, it’s still limited to our community of data visualization practitioners and enthusiasts. But I see Rob Radburn and Chris Love putting a lot of effort into their Data Beats investigations--which are by turns whimsical and biting, but always engaging; we all see people like Chloe Tseng and Olga Tsubiks spearheading formal initiatives to effect change with community-designed visualizations; we have individual practitioners like Lila Manheim, Ken Flerlage, Luke Stanke, and a host of others developing socially relevant and important work on their own. But where do they go? How do we get these great works in front of a wider audience? That’s part of my data goals for this year--figuring out how to get our community’s work to break out of our own bubble and get seen, engaged with, and passed along by a wider world.

The other part of my data goals is related to this, and that is: I want to figure out how to discover, support, and promote the other Tableau practitioners out there who don’t necessarily participate in the big community initiatives (the Makeovers, IronViz feeders, other “official” community projects), or who don’t participate regularly...but who are doing good, interesting work. Or, simply, who don’t play on Twitter. #TableauFF is meant to help us do that--but that requires all of us who are already “known” in the community to constantly be on the lookout for new people whose work we aren’t yet aware of. After all: someone brought each one of us into this community at one time or another. Someone saw our work and thought it was worth noting. Someone helped us get better. Someone introduced us to other people who could give us advice and support. If we’re not going to pay all of that freely-given capital forward, and work to bring the next wave of designers up with us, then what are we even doing?

So in two halves, those are my data goals for this year: actively work to develop the next cohort of data visualizers; and do what I can to get some of our community’s best work out into the wider world where it can have an even greater effect on our world.

 

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