Two Tableau Visuals a Week for an Entire Year. What did I Learn?
Updated: Jul 19, 2022
All 104 Tableau visuals I created in 2021.
Key Takeaways (TL;DR)
Understand the purpose of your visualization. Visuals can focus on telling a story or can be a simple tool to allow users to explore data. Many times it is a mixture of both, but understanding your goal in presenting the data that you have early on will save you both time and energy in the data visualization process.
Stay organized. One project, one folder. Properly label calculations, sheets, dashboard actions, etc. to help your future self understand what you did before. Staying organized also helps those who may look to download your workbook from Tableau Public to learn more about how you created your viz.
Know your data and your audience. Figure out the data that you have and determine the visual types that make sense given your target audience. Use your toolbox of data visualization techniques to communicate what the data is telling you in an easy to understand format.
Always be on the look out for data sets you can use. Looking to build your own portfolio? Create data visuals that you enjoy on topics that you are interested in. That will give you the motivation and drive to put in that extra ten percent to turn a good data visualization into a great one. You also might discover insights on something that you genuinely care about!
Use the #DataFam community. Whether it is looking up blogs, participating in community led initiatives, or simply looking through the visuals that have been shared on Tableau Public, there are so many resources out there that you can use to get inspired and level up your data visualization skills!
What did I learn from creating 104 Tableau visuals last year? A lot. Alright, thanks for coming to my second blog post! Just kidding, in this blog post I will be discussing what I took away from completing my goal of creating two data visuals a week for an entire year.
This piece will focus on the advice I have to give to both experienced Tableau users as well as those just starting out and looking to improve with the platform. This blog post touches on how to get data for projects, how to stay motivated, and some best practices to have when going through the data visualization process.
One of the most important things about data visualization is that you need data to visualize (wow, great insights Michael). Last year, I relied on a bunch of different sources to pull data from for visuals.
Here are a few go-to's I used last year that are #DataFam community initiatives:
Co-founded by Eva Murray and Andy Kriebel, MakeoverMonday has around 300 datasets to build visuals with. Each week a data set was shared with a visual that could be improved upon. The community would share their version of visualizing the data set on Twitter with #MakeoverMonday.
One of the pluses with pulling data from here is that you can go on to Twitter, use the advanced search feature, look up the hashtag for a given week, and view visuals from different creators to get inspired from (just be sure to give credit)! Below is a query you can use to enter into the search field on Twitter (this is specifically looking up visuals created for WK1 2021):
(#makeovermonday) until:2021-1-09 since:2021-1-03
Even though the initiative is no longer releasing data sets each week, there is still plenty of data to look through! Find something you think is interesting and start vizzing!
Back 2 Viz Basics
This is a new initiative led by Eric Balash that was created to help those just getting started with Tableau. Back 2 Viz Basics started with a teaser challenge in 2021 and now releases bi-weekly (every other week) data sets focused on a particular visual type. The first week focused on scatter plots and the second week focuses on dates & line charts.
You can search the hashtag #B2VB on Twitter to view different creators' takes on the same dataset, similar to the previous initiative. If you are a student and looking for guidance on everything Tableau, check out the Tableau Student Guide as well (maybe check out their most recent student interview while you're at it)!
Diversity in Data
Co-led by Autumn Battani and Eve Thomas, Diversity in Data provides data sets monthly focused on diversity, equity, and awareness. They have data centered around sports, humanitarian aid, mental health, and much more.
Last year, I was able to participate and create a viz looking at the accomplishments of Paralympic athletes. I hope to do more this year since the data shared is great to create visuals to spread awareness on so many important issues.
Other #DataFam Community Initiatives Worth Checking Out
Here are a couple more community led initiatives that I hope to participate in this year!
For many of my miscellaneous projects that focused on topics that I was personally interested in (mostly politics), I relied on news organizations, government websites, university databases, etc. with a focus on the credibility of the source. When on the look out for data, always be cognizant of where that data is coming from and ask yourself whether or not you trust it. (For many of the news organizations below, I would pull data by going to the source of the visual used in a given article I was reading.)
Some of my go-to's that I used last year for multiple visuals include:
The Washington Post (I actually visualized the results of a survey conducted by the Post in partnership with the University of Maryland that I helped write. It was part of one of my undergrad classes last year!)
U.S. Census Bureau (so much data to explore!)
With anything you are trying to achieve, you have to be motivated to put in the time and energy to create something great. As I mentioned in my previous post, I decided to make the goal of two visuals a week at the start of last year because I saw such amazing work done by creators in the Viz of the Day (#VOTD) series and I wanted to build visuals just like them.
This motivation changed as the year went on however. My focus on what others were creating was great to spark my interest in learning more about Tableau, but that spark would soon fade. I would say towards the middle of February, with the start of my final semester of undergrad, organizing events as a Tableau Student Ambassador, and starting a position as a Research Assistant at the University of Maryland's Government and Politics Department, building these visuals each week became increasingly challenging. I needed something more than just wanting to get better with the platform (which after 8 to 10 different visuals, was already the case). I soon realized that I would have to find a new source of motivation to stick with the goal and juggle everything going on in life.
Instead of trying to replicate and having my source of satisfaction in building visuals be dictated by what others within the community were doing, I decided to look at topics and visual types that I was interested in. Whether it was looking at the biases within the Senate or doing an analysis of 60 Minutes or understanding the provisions of The American Rescue Plan, I shifted my focus onto topics I wanted to learn more about and viewed Tableau as the tool to do it. (My viz on the American Rescue Plan was one of the first visuals I had done that I had put some serious time and energy into creating because I was curious myself what I was going to find.) I was no longer concerned about whether or not my viz would get likes on Twitter or favorites on Tableau Public, my main concern was whether or not I was learning something from the analysis.
This is what continues to motivate me to this day. I believe this shift in focus can help others maintain their drive as Data Analysts since the data tools we use are always changing, but our goal to find meaningful insights through data remains the same. If you are looking to build your own portfolio, look to create visuals on topics that interest you and that you want to gain insights from as it can tell others what you're passionate about while allowing you to pick up the necessary data skills along the way!
Having to stay on top of so many projects with limited time, I soon realized I had to work smarter, not harder when it comes to data visualization (I know, it's cheesy). Here are a couple things that I found helped me last year to stay afloat and achieve my goal!
Before you actually start building a visual, make sure you have some idea of what you are looking to visualize. If you need to explore the data first to see what stories are there to tell, do that in a couple of sheets and then move to the dashboard. Far too often last year, I would have to spend needless time altering a dashboard and the formatting of different sheets since I hadn't really considered what I was planning on showing. Having a general idea will save you tons of time since we all know how easy it is to format in Tableau...okay on to the next one.
Always keep your audience in mind
Think about who would be interested in viewing the data that you are visualizing. Is it experts in the field? Future employers? A general audience? Are you going for a complex viz with abstract representation to impress fellow Tableau enthusiasts or are you trying to share insights and spread awareness to non-data people about an important issue? Remind yourself that you are both a communicator and translator. You have to speak your audience's language and translate what the data is telling you into real world application.
Picking visuals and concepts to discuss rely on your audience's knowledge on the subject as well as their familiarity with data. This practice will also help you in your professional career when working for clients or building deliverables for stakeholders as they are the ones using these visuals and rely on you to translate the data into meaningful insight!
Know your data
Before you try to visualize a data set, make sure you have a full understanding of what your data is. What it is measuring? What do certain variables represent? Having thorough knowledge of the data you are working with and the context at which you are working with it can help you with the insights and stories you are trying to tell with your data visualization.
Stay organized within Tableau
This one took a while for me to get in the habit of doing. Properly label your calculations, your sheets, your dashboard actions, etc. If you are working on a pretty complex viz, label the items on your dashboard. Far too many times I would go back to a previous viz and have difficulty remembering what I did exactly. Getting in the habit of properly labeling things will save you time when you're finalizing your visual and for when you have to go back to look at something months later. Building this habit also helps those who may want to learn more about your viz on Tableau Public, as they will find it easier to follow along with your process when downloading the workbook!
Stay organized outside of Tableau
I have a system where I have one folder for every project on my computer with a simple folder hierarchy. This way I can save the workbook, data files, images, etc. in one spot that I can easily go back to and find the project quick and easily. Keeping things in order on your computer also helps with files not being moved around, potentially breaking your data sources or images being used visuals.
Don't always harp on the small things
Some of you may consider yourselves perfectionists, I certainly consider myself one. It's great having attention to detail and making sure everything is working the way you had envisioned, but many times you come to a little snag and something doesn't work out. Having limited time to work on these projects, I would often focus on minor details that are great "haves" in a visual, but would take considerable amounts of time to figure out, often taking away from the actual analysis. If something isn't working, adapt your visual and move on. Come back to it another day or try it in another project when you have the time!
And that, my friends, is what I learned from doing two Tableau visuals a week for an entire year. Told you it was a lot! Thank you for reading what I had to share! Moving forward, I have some thoughts on a series of posts walking through past visuals I have done (I know there have already been a couple requests to explain the spike map visual I did a few weeks back, hopefully I will be able to write that up soon).
If there are any other topics you are interested in hearing my thoughts on, reach out to me! You can find me on Twitter, LinkedIn, or Instagram. You can also email me at firstname.lastname@example.org or use the 'Contact' page on this website!
By Michael Dunphy
Published Jan. 21, 2022