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Join the Boulder Community for Analyze Boulder Meetup:


As always, great beer will be on tap from Vindication Brewing, thanks to our Startup Colorado Community Fund Grant. 

Phil McCready from GrowStrong uses advanced analytics to discover distinct growth patterns and best fit prospects for economic development in unique communities, then helps empower decision makers with the data needed to invest in projects that foster job growth and prosperity.

Kyle Campbell will talk about how the mobile game analytics industry works and the types of metrics monitored.

The City of Boulder wants to identify community priorities for action and tools to address Boulder's housing options, and would like help refining how to visually present data to ease residents into the challenges of housing. City representatives will present the data and first draft of a 3 Minute Housing Explainer, then brainstorm how it can be improved.

Delighted to see entries from Boulder in the Wiki Data Viz Contest sponsored by TableauPublic. Check out entries from #wikiWilliam2, #wikiSteven, and #wikiChrisC1 at  This contest builds on twitter love, so give these guys some if you like what you see!  Voting goes through Thursday.

The competition for Iron Viz qualification has begun! In case any of you don't know about the Iron Viz, it's an "Iron Chef"-like competition that Tableau holds every year at their annual conference. Here's a blog post that talks a little more about it: Iron Viz Competition 2015.


Everyone has submitted their visualizations for this first round using only data from Wikipedia, and there are a lot of good ones out there to learn from. I know that I'll personally be downloading several of them to learn from, maybe you'll find some things you want to learn about too!


Iron Viz Wiki Data Submissions


For my submission, I chose to manually scrape the "Notable Deaths" data from Wikipedia, a task which ended up involving way more data cleaning than I thought it would be. The data resided in 29 individual pages, links to which can be found in this one central page. Unfortunately, although the data was roughly in the same format from page to page, it differed just enough to make it difficult to structure into a Tableau-friendly format. The process I went through was a long combination of manual work and Python scripting, in order to turn the data into a consistently-structured .csv file that could then be loaded into Tableau. (Headers: Date of Death, Name, Description, Birth Year, Age)


After finally getting the data into Tableau, I decided to try to parse out the Nationality, Occupation, and Cause of Death for each person using a long series of IF / ELSEIF statements. (I also used CASE / WHEN statements for a few applications. I prefer to use these since they're more compact, but they couldn't do the string parsing that I wanted.) Not a perfect method because of complexities within the data, but it ended up returning some very interesting results nonetheless! Check out the "About" tab in the viz for more info on the methodology. (The viz is below, but here's the Tableau Public link if you want.)


By the way, if you aren't already active in the Tableau Public world, I definitely recommend finding and following some bloggers! I recently had the opportunity to talk with Jewel Loree, and she is always coming out with plenty of interesting vizzes that will improve you analytically and creatively. (VizCandy and Paint By Numbers are a couple others I try to keep up with, as well.)


Happy exploring!


Steven Rouk

A few weeks ago, a security researcher released a dataset of 10 million usernames and passwords that he'd scraped from places online. (He cleaned them up a bit, and they're probably all dead, so don't worry.) Since a release of that magnitude hadn't really been done before, I thought it would be really interesting to analyze the data in Tableau and see what insights I found.


The results? Lots of weak passwords, a smattering of profanity, and even some Bieber references.


The full blog post goes into more detail, including how to use Tableau 9.0's new support for regular expressions (which are completely and totally awesome). Here's the link – 10 Million Passwords Analysisor just click the image below. Make sure to explore the viz for all the cool insights! (Tab #3 will let you search a subset of usernames and passwords for any words you want.)


blog - viz screenshot smaller.bmp

Tableau is taking their show on the road - and you're invited! The much anticipated launch of Tableau 9.0 is almost here, so get your work done early and come see how "Smart meets Fast" at the Tableau 9.0 Road Show on Thursday, March 19 at the Inverness Tech Center.



9.0 Showcase - Doors open at 1pm

We are excited to welcome Tableau to Denver (we are 1 of only 19 cities on the tour). Starting at 1:30, this free event has three hands-on Tracks for newbies, users, and executives. Whether you are discovering Tableau, looking to expand your knowledge, or wanting to Network - this event will not disappoint. We would love to see you there; be sure to let us know if we should be on the look out for you. Learn more and register at:


Launching BTUG - Boulder Tableau User Group

Stay for the launch of BTUG at the Tableau User Group MeetUp from 5 to 7 (with food/drinks), we promise it will be fun! We are looking to kick off membership and drive a community of passionate learners and mentors, where both data geeks and non-number crunchers can feel confident! Can't make the meeting? Join us, we will host the first meeting in 2Q.

Steven Rouk

MetaViz of the Day

Posted by Steven Rouk Mar 2, 2015

Hello everyone in the Boulder Tableau User Group!


This content page is looking pretty dead, so I thought I'd write a post to add an infinitesimal amount of life here. (Would that make the page "undead"? Yikes, zombie page!)


We lovely folks here at Boulder Insight like to keep up with the "Viz of the Day" publications from Tableau Public, and we thought it might be Viz-of-the-Day-worthy to analyze all of Viz of the Days! (Vizzes of the Day? Neither sounds good.)


So, without further adieu... the MetaViz of the Day!


Some interesting things to look for:

  1. Sports holds the title of most-talked-about-topic, and it's also the category that has seen the greatest increases in the past couple of years.
  2. John Schoen and Ramon Martinez have a whopping 35 vizzes between them. If you want to get on Viz of the Day, apparently they're the ones to learn from!
  3. The number of Economy vizzes published per year has decreased the most consistently out of the categories. Perhaps this is because the economy is continually doing better from year to year? Or maybe people have lost all hope and choose to watch football in despair?
  4. The number of vizzes about Culture spiked in 2013. Why was 2013 such a hot year for cultural topics?



Feel free to let us know of any other insights you find! And maybe one day, your viz will be listed here too...


Happy Visualizing!


Steven Rouk

Visualization Scientist

Boulder Insight