Tableau Certified Data Analyst – Exam Resources

Exciting news to share – I recently passed the Tableau Certified Data Analyst Exam! 

For those of you not familiar with this certification, it is offered by Tableau and is valid for two years. Since mine had expired and my employer required it to be renewed, I found myself back in study-mode to prepare. There are several excellent resources available online – here’s a list of my go-to’s: 

Tableau’s Exam Guide

This link provides an overview of exam format, grading, and sections to be covered on the exam. Note: the exam is in three sections, and once you complete a section you cannot return to it later. Be sure to review each section before pressing “Finish” and moving on to the next section. The exam is closed-book, meaning you cannot search for answers online, or login to Tableau to verify.  There is one hands-on section which requires you to complete tasks within Tableau Desktop. 

Study Guide from Learning Tableau

This is website provides handy links to Tableau documentation for all sections of the exam. I found Domain 1 focused quite a bit on Tableau Prep and Custom SQL, so if you mainly use Tableau Desktop in your daily work, be sure to review these concepts. 

Practice Questions and Exam Overview

This is the perfect resource to review a sample of typical exam questions and familiarize yourself with the format. The wording of questions and multiple-choice answers can sometimes be tricky, so practicing ahead of time is well worth the effort!  During the exam I reviewed all of my answers, which was helpful as I caught a couple that needed correcting after re-reading the question.

#Datafam blog posts from CJ Mayes, featuring Deborah Simmonds and Mehras Abdoli, and Ann Pregler

Last but not least, this round-up would not be complete without mentioning these #Datafam links – my go-to’s for learning all things Tableau, 365 days of the year!

Andy Kriebel



The Flerlage Twins

Felicia Styer

Kim Unger

Bridget Cogley


Overall, I found the experience to be challenging and reaffirming. It gave me an opportunity to brush up on some concepts I don’t use daily and it was a good test of my Tableau knowledge.  Please feel free to reach out if you are planning to take the exam  – happy to share my tips & knowledge! 

Pep Talk Generator: Life is hard, giving yourself a pep talk doesn’t have to be.

Growing up, my dad gave me the best pep talks. One of his favourties was “Keep your stick on the ice.” Not surprising given his lifelong love of hockey. My Dad passed in 2013, and I miss his pep talks. This pep talk generator helps to partially fill that void, and it is one way I can share the joy he found in lifting others up.

So, let’s get down to the Tableau part, shall we? Building this pep talk generator in Tableau required using a variety of Tableau techniques — here’s a peek under the hood:

Each pep talk is composed of four separate string values. This gives the dashboard over 100,000 possible pep talk combinations. To offer the choice between the create your own pep talk or randomly generated pep talk, I employed parameters & calculated fields. There are four string calculations for the create your own and another four calculations for the random version.  For those of you keeping score at home, that makes eight calculations.

Pretty straight forward so far, agreed? Feel free to download the workbook from Tableau Public and follow along if you wish!

Both versions of the pep talk generator – create your own and randomly generated – use parameter values in the string calculations to change the text that is shown. Create your own has four parameters, one for each string calculation. Random also has four parameters, one for each string calculation. (Add 8 parameters to the score sheet!) However, the method by which these parameter values are updated differ. Let me explain:

For the Create Your Own version, the values in the parameters are updated using Tableau’s parameter control boxes, which are visible to the dashboard user.  In other words, when the dashboard user interacts with the parameter control box, the value in the parameter changes and updates the string calculation for that portion of the text.

The randomized version also uses four parameters, one for each string calculation, however, these parameters update when the workbook is opened using a different set of calculations. The “default when workbook opens” calculations utilize the function RANDOM() to randomly assign a value between 1-18. 

For those of you keeping score at home, we now have 12 calculations and 8 parameters. Could this be done with fewer calculations? Yes, probably. In fact you could combine the string calculations and thereby reduce the number of calculations, but I prefer having simpler, shorter syntax over nested calculations.

Now that we have the mechanism by which both sets of string calculations will update, and we can use these calculations to build the sheets by placing them on the text marks card. I used two separate sheets, one for the create your own pep talk, and a second one for the random version. I also built two more sheets which I named “button random” and “button create your own” that are used on the dashboard to toggle between the two versions.

You may be wondering how does the dashboard know which sheets to display? Dynamic Zone Visibility and Parameter Actions, FTW!  To employ these techniques, the dashboard utilizes another parameter with two values: Random or Create Your Own, to identify the components needed for each version. The components are as follows:

> four sheets: randomly generated text, create your own text, button random, button create your own


> four parameter control boxes that drive the create your own version

On the dashboard, you must assign the “Control visibility using value” to each component, or in the case of the parameter control boxes, the container that holds the components. Lastly, parameter actions drive these components (aka zones) to update dynamically when the dashboard viewer clicks on the “button” sheets. Naturally, there are a few more calculations needed to achieve this functionally, as well calculations for formatting the tooltips – all in, the total number is 22 calculations and 9 parameters! It sounds like a lot, but with consistent naming and a well-laid out plan, the dashboard build is very do-able.

I hope this Pep Talk Generator lifts you up and gives you the motivation to keep going. And if you know someone that needs a pep talk, please pass it on.

Viz built by: Sarah Pallett. Inspiration: David Pallett

The Value of White Space

I love adding white space or “empty space” to a dashboard. It’s like having a desk that is clean & uncluttered instead of covered in stacks of papers and knick-knacks – it’s peaceful and makes a dashboard feel more “approachable”. It is an under-rated technique that deserves the spotlight.

The September #EduVizzers Challenge on Book Bans was the perfect opportunity to play with this technique, AND the fact that Iron Quest’s White Space Challenge was happening concurrently made the timing ideal. During my development process, I identified 5 distinct metrics that deserved equal attention.  Rather than combining all 5 bar charts in one view, I utilized parameter actions and dynamic zone visibility to allow the end-user to view each chart one at-a-time.  This gave each visual a dedicated space and breathing room to let each metric make a statement.  I know what you’re thinking — in the real world we don’t always have the luxury of showing one chart at a time. Often the visuals need to be side-by-side to assess the metrics in tandem.  In those instances, you can increase the padding around each object.  This is a more subtle way to add white space and one of my default formatting techniques. Outer Padding adds space between two dashboard objects while Inner Padding adds space inside the object’s wireframe. Here’s a screenshot with exaggerated padding to illustrate the difference:

And if you’re curious about school book bans in the US, here’s a viz for you:

Happy Vizzing, and happy white-spacing!

Community Wednesday: A sneak peek into one of our best practices at DataBrains

A quick glance at my calendar reveals a recurring meeting every week named Community Wednesday.  Yes, it’s another zoom call, but it truly stands apart from the rest. 

Originally designed to help grow the skillset of our emerging talent, it has evolved into one of our best practices.  It is a dedicated hour each week for the Tableau Developers at DataBrains to come together to share projects, troubleshoot technical issues, collaborate, brainstorm, and upskill. Sounds like a lot in an hour, doesn’t it? As Brainiacs, the conversation & exchange of ideas moves quickly, making it a fun, fast-paced meeting.

Each week the topic of conversation will vary – some weeks a Brainiac will share a work-in-progress, other weeks we will solve challenges from the wider Tableau Community, namely WorkoutWednesday, Back2VizBasics, and Preppin’ Data.  

Both experienced & emerging talent participate, which allows for the transfer of knowledge in a supportive and collaborative environment. The weekly cadence keeps the discussion relevant, timely, and in sync with client deliverables.  Last but not least of all, it fosters a sense of community among teammates, which Tableau recognizes in the Tableau Blueprint as a core component of successful data-driven organizations.  

I hope this inspires your organization to establish your own best practice to engage & support your Tableau Developers in a collaborative way.  Let your imagination lead the way — how does “New Tip Tuesday” or “Lunch & Learn Fridays” sound?

Winning the Ted Lasso way: it’s all about teamwork 

In March 2023, Anne-Sophie and I (Sarah) jointly published a visualization on Ted Lasso and his pop culture references in Season 1 and 2. As such, this blogpost is co-written by the both of us to share our collaboration process & highlight the reasons that contributed to the success of this Viz. (Sarah’s Viz link, Anne-Sophie’s Viz link)

“I think things come into our lives to help us get from one place to a better one.”  

(Ted Lasso S2 E1)


At the heart of the success of this viz is collaboration. Anne-Sophie and Sarah met in the Spring of 2022 through Nicole Klassen’s #VizCollab initiative, a program that connects individuals who wish to collaborate on data viz projects. 

So where did we begin? 

Our collaboration kicked off with a zoom call, during which we chose the topic of our visualization: the TV series Ted Lasso. We noticed the show’s dialog is rich with pop culture references, and wondered what these references tell us about his character, upbringing, and passions? 

The zoom calls quickly became a weekly occurrence. Not only did this cadence help to keep us on track, but it facilitated brainstorming & idea generation that truly gave the project some momentum.  

We established a need to build our own data set by re-watching Seasons 1 (Sarah) and 2 (Anne-Sophie). There are a few articles and videos listing the show’s pop culture references but none of these provided an exhaustive list, not even in the IMDB connections pages (which have been so helpful for Anne-Sophie’s Buffy project).

Re-watching the episodes was super-fun and easy, but the real work came when it was time to build out the metadata to include country & year for each reference, as well as categorize them by topic. A shared Google spreadsheet was an essential tool that allowed us to collect the data in a standardized format. To ensure accuracy, we sourced the actual dialog from an online transcript website. Wikipedia was our go-to resource for researching the significance of each reference, thereby uncovering the witty & cleverness of the show’s writing staff, plus a few were a tad bit obscure!  As you can imagine, this metadata collection process took a great deal of time, and we were relieved when Season 3’s release date was postponed.

As work progressed, we explored some possible chart types in Tableau Desktop, and shared those using Tableau Public’s Hidden Viz feature.  

To guide our design & colour choices, we decided to tap into the Ted Lasso brand by incorporating key visual elements from the show. For example, the opening sequence with the blue & red stadium seats gave us the idea to visualize each reference as one stadium seat, with the interactivity of the viz changing the seat colour. 

We also played around with the concept of Ted Lasso’s yellow “Believe” poster and committed to that design element when a teaser for Season 3 featuring the poster was released. 

The blue, red, & yellow colour choice was a no-brainer (on brand) and yet challenging at the same time (balancing three strong colors). As such, we toned down the red, and used the yellow background only on the intro & outro sections. 

All the design (background images, text) was done in Figma, with the help of Noun Project icons (if you can afford, a paid license is a great investment).

With our data set complete & ready, now came the question: what to do with 200 stadium seats? 

Inspiration & Feedback from the #datafam

Inspiration struck when Anne-Sophie shared Simon Rowe’s Titanic Viz. Brilliant! We would  recreate the opening sequence, hence the animation in both the placement of the seats and the colours. We also gleaned inspiration for changing background images from this same viz, and the technique to do so from Will Sutton’s tutorial. Additional techniques learned from WorkoutWednesday were utilized (hello, dynamic zone visibility and parameter actions). Together these components satisfied one of our main goals: a fun, story-telling exploration of the topic. 

But wait, there’s more! Great vizzes incorporate feedback from Tableau Ambassadors and seasoned developers alike, so we tapped into the #datafam resources such as #VizOfficeHours with Michelle Frayman and Nicole Klassen, and reached out to individuals we admire & respect (looking at you, Bridget Cogley and Kim Unger). This feedback took our viz from good to great, and we appreciate their time immensely.

A mutual desire to do great work

For both of us, taking time to add the finishing touches was an important step in the process. This involved incorporating various techniques including: hiding Tableau’s “blue highlighting” when you cannot float a blank on top, using a highlight action to make a chart “unclickable”, and creating a parameter with a hierarchy, all tips & tricks we’ve learned from the #datafam. 

Essential to this workflow process was our “to do list”. As you can imagine, a viz of this scope encompasses a million little details, so this tab in our shared Google spreadsheet became our place to capture notes, link online resources, and assign tasks….right down to the smallest of details such as fixing typos.  

Final notes & lessons

You may have heard that collective sigh of relief on March 6th when we both pressed “publish workbook” and officially shared our viz on Tableau Public. But our collaboration did not end there! We coordinated the timing & content of our social media posts and discovered a delightful bonus – our collaboration extended our reach to a wider audience. Self promoting your work can seem cringe worthy, so collaborate: you will be cheering for somebody else and with somebody else!  It truly doubled the joy & satisfaction. 

Our Ted Lasso Viz is a testament to the fact that success comes from hard work and a lot of luck. We had the same level of expectations & willingness to do the work to craft a viz we would be proud of. And our skill sets were complimentary in such a way that it enhanced the viz immensely, making the process a true collaboration. As far as luck goes, our pairing through the #VizCollab program was indeed lucky, or as Ted Lasso said himself,

“I feel like we fell out of a lucky tree, hit every branch on the way down, ended up in a pool full of cash and Sour Patch Kids.”

(Ted Lasso S1 E6)

Chasing The Great One: Ovechkin vs Gretzky

This post originally appeared on DataBrain’s blog in July 2022. Enjoy!

Growing up in Canada meant hockey was a central part of our lives. My Dad was a star player in his younger days and was the captain of his college team, the University of Guelph Gryphons. Given his love of hockey, he often referenced sports metaphors when teaching life lessons to me and my brother. Case in point: his favorite way to end a pep talk? “Keep your stick on the ice”. 

My hometown was a short drive from Wayne Gretzky’s hometown, so you can imagine the excitement when the young player wearing #99 hit the big leagues. He became a national hero for a whole generation of Canadians from coast to coast, and deservedly earned the designation “The Great One” just as fast as he could skate circles around the opposing team. 

Naturally, my interest was piqued when an article caught my eye by sportswriter Tarik El-Bashir titled “Alex Ovechkin’s contract with Capitals gives him a chance to catch the great one for NHL goal-scoring record”. Could it be that another hockey player was within reach of breaking #99’s all-time goal record, one that has been held by The Great One for my entire life? Am I witnessing sports history in the making!?!

A little digging into some hockey stats revealed some intriguing data points that became the inspiration for this viz. I combined multiple data sources to put the magnitude of this potential achievement into context. Goal scoring became the focus of this viz and allowed me to answer the following questions:

How do Gretzky’s and Ovechkin’s goals per season compare?

Are there any other active players close to breaking The Great One’s record? 

Who among the top goal scorers has earned the most $ per goal?

Who has scored the most goals, in the shortest period of time?

Last but not least, as a nod to my home country and my dad as a young player – where do these top goal-scoring players first learn to lace up their skates?

Keeping best design principles in mind, I chose a red-black-grey color scheme to limit the clutter, while letting the emphasis on Ovechkin’s red team color tell the story.  A bar chart was chosen to quickly display the rank of the top 50 goal-scorers, with the length of the bar allowing easy comparison of total career goals. Clicking on the bars identifies the marks on the adjacent graphs, adding an element of interactivity to the viz. Scatterplots were employed to compare the metrics “salary vs goals scored” and “years played vs goals scored”. Tableau’s tooltip features are enabled on all graphs, allowing the audience to reveal additional, relevant details. Bar charts with timelines on the X-axis were generated to showcase a side-by-side comparison of the goals-per-season for Gretzky & Ovechkin, with an average goals-per-season reference line and color denoting the challenge Ovechkin faces in the years ahead. Last but not least, data calculations were done at the source level when possible to optimize dashboard performance, including calculating salaries in current dollars. Click here to explore the viz.

As I watched the NHL draft unfold this week, I was compelled to revisit the viz and answer one more question: Does draft order matter? It doesn’t appear so – only 9 of the top 50 goal scorers were drafted first (including Ovechkin) and interestingly, Gretzky was not drafted at all! You can read that story here. I guess what really matters at the end of the day is another metaphor my Dad was fond of saying “You always want to score the first goal, otherwise you need two to win.”

Good luck to all the rising stars who realized their dreams at the NHL draft this week, and best of luck to Ovechkin on his quest to surpass The Great One. 

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