Spencer Baucke Bio
Raised in Loveland, OH, Spencer Baucke has a B.A. in Economics from the University of Colorado and an M.S. in Finance from the University of Cincinnati. Spencer is a Sr. Analytics Engineer at GE Digital in Cincinnati, OH. His work experience includes several years in banking as well as a stint at the City of Cincinnati’s Office of Performance and Analytics. He has also worked closely with the education non-profit StriveTogether in a consulting role for the past few years. Mr. Baucke is a regular contributor to Tableau Public and the larger Tableau community via Twitter. He also is a co-founder of the Tableau/Twitter initiative, #SportsVizSunday.
In his free time, Spencer enjoys staying active in the community. For the past five years, he has had the immense honor of coaching varsity football at Shroder High School. He is also a Public Allies mentor and is active in his local community council.
Spencer noted that he would be remiss if he didn’t mention his wife Nia, who has put up with him spending way too many Saturdays in front of his laptop learning Tableau and other data analytics tools. He also notes that she is the most amazing wife in the world! They also welcomed their son, Nolan, to the world in September, as you can see by the bags under their eyes.
Michael: Hello Spencer. I really like your Sports Dynasties data visualization you published on Tableau Public.
Can you please tell my readers the process you used to find the data you needed, design the dataviz, and finally, build it in Tableau (including the tricks you used to create this unique dataviz)?
Spencer: Thanks, Michael! I first got the idea of looking at the dataset that Corey Jones loaded to our data.world site for January’s #SportsVizSunday challenge. Most of my sports vizzes start off as bar arguments, this one being no exception. The word dynasty is thrown around a lot during sports conversations so I wanted to see if I could somehow quantify a dynasty using the data set Corey had put out. There was some good back and forth on Twitter with some people from the Tableau and #SportsVizSunday communities about what a dynasty was so I took that and ran with it.
As far as building it, I first laid out my criteria and identified the teams that met it in Excel. Then I went back and researched each team so I could name the dynasty appropriately. I think that’s some of the fun of sports vizzes though because it was so fun to go back and see some of the great teams that I had either forgotten about or didn’t live to see. I think part of that is growing up a Cincinnati Reds fans where you’re indoctrinated to have a strong sense of reverence for the Big Red Machine and all they did.
Once I curated the data I used calcs from Toan Hoang’s Tableau magic blog post on arch charts. Design wise, I have a tendency to want to put too much data into a viz, so I was looking for a more simplistic way to display data. I really feel like Ken Flerlage does that better than almost anyone, so I definitely spent some time looking at his Tableau Public page when making this viz.
Michael: Can you tell my readers about your Tableau/Twitter initiative, #SportsVizSunday?
Spencer: #SportsVizSunday is a twitter/tableau community of sports and data lovers that provides a way for people to engage and share sports related data visualizations. Every month we post a data set on our data.world site (data.world/sportsvizsunday) for people to work with. When you complete a viz please post it on the data.world site as well as share on Twitter tagging James Smith (@sportschord), Simon Beaumont (@Simon Beaumont04), and myself (@jsbaucke) and use the hashtag #SportsVizSunday. This way we make sure to see your viz and are able to share it with the broader #SportsVizSunday community while providing feedback where appropriate. In addition, you can also share a viz using the #SportsVizSunday hashtag regardless of day or month to promote a sports-related viz that you want to share with the community.
We have been really fortunate to have some big name in the Tableau community including a few Zen Masters, Tableau Ambassadors, and other well-known community members supporting our initiative. Our first year (2018) culminated in a speaking slot at Tableau Conference in New Orleans. The support there was overwhelming. We were just hoping that a few people actually showed up to hear these three goofy dudes talk, but we actually ended up having to turn people away due to capacity. At the end of the day, it’s the participants that make this thing go, and we are so appreciative of all of them!
The line for #SportsVizSunday’s presentation at TC18 above. The three of us below.
Michael: Can you tell us three of your favorite Tableau Desktop tips and tricks?
Spencer: Honestly I’m a horrible tips and trips person (lol-ing literally). I still look up Ryan Sleeper’s blog post on trellis charts every time I make one, so I’m generally not one of those people who finds some cool feature in Tableau no one knows about. Most of the time its the opposite, I have to read a Lindsey Poulter blog post on Set Actions ten times before I understand it.
If I had a trick it would be to start bringing in your fields using a right click instead of left to eliminate time for how you want that field to show.
Hard work and time are undefeated.
If I had a tip it would be to spend a lot of time in Tableau. Set out and try to understand how different chart types are built. If you see a viz on Tableau Public that makes you go “wow, I could never do that,“ download the workbook and figure out how they made it. Hard work and time are undefeated.
Michael: I am very impressed with how involved you are in your community and all you do for social good. Let‘s discuss each topic one at a time.
Can you tell my readers about StriveTogether and how you are involed with them?
Spencer: StriveTogether is a local non-profit that partners with local school districts and service providers to try and ensure every child succeeds from cradle to career. They do a lot of outstanding work with Cincinnati Public Schools and the northern Kentucky districts, Newport Independent School and Covington Independent schools. The past few years they have been heavily leveraging Tableau as their primary data analysis and visualization tool to help them understand things from testing results, school and community survey data, and regional/districts trends. As a consultant, I help them maximize Tableau’s potential by building out template dashboard and ad-hoc dashboard as well as helping out with any problems they may have visualizing their data in Tableau.
Funny enough, StriveTogether is where I got my Tableau start. They originally had me helping with some of the data work they were doing in Excel when the person who I reported to at the time, Geoff Zimmerman, told me I should check out this cool data tool called Tableau. He sent me to a training class at the University of Cincinnati lead by none other than Zen Master Jeff Shaffer, and the rest is history. Jeff’s energy and passion about Tableau were so inspiring that I knew I wanted to pursue learning more about this tool. Between Jeff’s training and using Tableau with StriveTogether, that’s really where I built my foundation of Tableau knowledge.
Michael: In addition to working a full-time job in IT, you also coach varsity football at Shroder High School in Cincinnati. Wow, that must be a lot of work. Can you tell my readers what it is like to coach varsity football and how you apply what you do in business intelligence and analytics to coaching football?
Spencer: For those not from Cincinnati, high school football is huge here. Friday nights for me as a kid meant going with my dad to see the local high school teams play, so it has always been a big part of my life. I feel really fortunate that I’ve had the opportunity to coach such fun and hard-working kids. Getting texts from old players and having them drop by on break from college makes all the time invested seem worth it.
During my time at Shroder, we hosted the first home playoff game in Cincinnati Public School history, which had to be my proudest moment as a coach. We ended up losing the game but being outsized, outnumbered, out funded, out everything’d, and the fact that my players didn’t back down when times got tough taught ME a lot.
We definitely tried to use analytics during one season especially, but with my time crunched as it was we never truly got to use it as much as we would have liked.
Michael: You mention that you use other programs such as Spotfire and OBIEE along with Tableau at work. Can you compare and contrast the three programs?
Spencer: I feel like I could write a 10 page paper on this topic. Maybe I should blog about it or something. The three programs are so different, and they all have their strengths. During my time at GE I have used all three on the same data sets as well so I’ve gotten an apples to apples view of it. I’ll try and do my best explaining the pros and cons.
User Interface: In my opinion Tableau is by far the most user-friendly. Even the layout itself of okay, here are your worksheets which you build individual charts and metrics into, then you take those and build a dashboard, that makes sense to me. Spotfire’s user interface is similar, but it’s also greatly different. Every tab is a dashboard, so you add dashboard elements to a tab instead of adding worksheets to a dashboard. A lot of the formula syntax is similar as well. It took me about two months to be functional in the program having already known Tableau. OBIEE is completely different and the least intuitive from a user perspective. OBIEE’s interface is much different than the other two but conceptually you’re able to build different views of your data then bring those together into a dashboard view. Navigating through the different screens in OBIEE is also way less intuitive in my opinion.
Viz Capabilities: Tableau is the best in this category by far. Google “best Tableau viz,” then do the same for Spotfire and OBIEE and you’ll understand what I mean. The flexibility of Tableau is unmatched with Spotfire coming in a solid second. If you really want your Spotfire viz to come to life you will need to use Java scripting as some basic charts types like pie charts are not able to be done with default chart types. I should note that I’m not endorsing pie charts as a preferred chart type, but it is often requested from process owners and so you need to at least be able to do them. OBIEE again is third on this list for me. Their presets are limited and in general, the charts are not aesthetically pleasing. Having said that, I did get to play around with Oracle‘s newest Data Visualization (name of the tool) edition and it is very comparable to Tableau in its ease of use. If you are going the Oracle route I would suggest the DV Desktop.
Data Sizing/Render Times: The biggest hurdle I’ve jumped through with Tableau is its time to render large data sets. When I say large I’m talking about querying a data lake view of 100M+ rows that is several hundred columns wide. I have read a ton of blogs and seen conversations about this topic on Twitter about how a lot of Tableau’s rendering ability is based on the back end architecture of your view. While I completely agree with this, I have tested all three products on the same data sets and concluded that Tableau takes the longest time to render a view of the three. Unlike Tableau, Spotfire is able to cache results of queries so when you run a repeat query the viz renders almost immediately. OBIEE, which is strongest for running table-like reports (often for export), can query these rows fairly efficiently as well. In terms of ranking them on rendering time I would go Spotfire, OBIEE, then Tableau.
Obviously, each person has their own preferences and experiences, and each tool has different use cases in which it would excel, but those are my overall thoughts. And Tableau obviously rocks!
Michael: Since you are very knowledgeable about sports, I have to ask you this burning sports question I have. I am a life-long Detroit Lions fan (I grew up in Detroit). What do the Lions need to do to be playoff contenders?
Spencer: As a Bengals fan, I am part of a fan base that can say they understand your pain. I am actually a part-time Lion’s fan myself as my father-in-law played for the Lions for several years in the late 80’s (Jimmy Williams, trading card below). To be honest, I have no idea what they need to do!! Win more would be my answer lol. I know a lot of analytics people would say don’t invest in running backs, go for it on 4th down, and go for 2 pt conversions more often.
Michael: What is next on your “To Do” list? What can the Tableau community expect to see from you in the near future?
Spencer: I guess this platform is as good as any to announce that I am actually taking a new job at Tessellation starting in February! I am super excited to be joining Luke Stanke, Steve Fenn, and Co. at this amazing company.
In terms of goals for 2019, I want to blog more about Tableau. I will continue to help run #SportsVizSunday and in my free time, I want to keep focusing on vizzes that I am passionate about. I’m also working on setting up a data analytics after-school club at the school I coach football at, so hopefully, that gets off the ground soon. Also, if anyone knows the secret to being a Featured Author on Tableau Public let me know, that’s on my list of goals for 2019.
Thanks so much for interviewing me Michael, I really appreciate everything you do in the community!