Dash(board)ing Through the Snow

by Vivian Ng

I originally posted this on my own blog (VNGLOOKUP) on December 28, 2022. At the time, I had just applied to the Data School New York’s third cohort and was going through the interview process when I started VNGLOOKUP on a whim. The informational dashboard I created for the DSNY application was the first one I ever made, and I enjoyed the process of dashboarding so much that I turned to another of my loves (writing) to talk more about how I did it.

I’m reposting this entry here, as I thought it’d make a fitting first post for the Data School blog as a new Data Schooler! Plus, it’ll be fun to look back on this first entry and see how much I’ve grown during my time here. While I’ll be cross-posting on both the Data School and my own blogs, make sure to check out my own blog for other posts, as any non-Tableau/-Alteryx entries will be found there!

Something I really love to do is tell stories, so I was stoked to start telling them with data, too! I made a dashboard about HIPAA breaches on Tableau Public recently and had a great time putting it together, so here are some tips from my experience with it.

Excalidraw was particularly helpful for planning it (I’m very much a planner at heart), but it wasn’t actually where the planning began. Just like with writing, the planning began with brainstorming.

I used Excalidraw early on in the planning process, but I plan to bring it in later on when I make my next dashboard, as I ended up deviating a fair bit from what I sketched up. I’m not sure why I resisted doing so initially, but once I approached creating the dashboard the same way I would any story, the rest of it came together quite smoothly.

I broke it up into five stages: brainstorming, outlining, visualizing, storyboarding, and dashboarding.

The Process


You’ve completed your data cleaning, exploration, analysis… Now you’re ready to start translating the insights you gleaned from the data for your audience! Brainstorming is sometimes the most difficult part for me because I like being organized, and brainstorming is all about just throwing stuff out there and seeing what sticks.

I strongly recommend brainstorming on paper or a blank document, away from all the charts you made in the process, so that you don’t get tempted to just Frankenstein-stitch your graphs together. In my experience, stories made this way aren’t as cohesive, and it’s easy to lose track of the main idea.

Start with the insights you uncovered in your exploration/analysis of the data. What stuck out to you? What points do you keep returning to? What three facets of the data do you want to focus on (approximate number)?

  • For example, my talking points for my dashboard were:
  • HIPAA breaches are on the rise
  • Impact of breaches on states varies greatly
  • Hacking/IT incidents are the most common type of breach

I like starting with the insights/talking points because they narrow the scope of the main idea or big question, allowing you to word it accordingly. Once you’ve articulated the main idea for your audience, you can then start coming up with ideas for your story’s hook or angle.

  • For example, my big question was: How do HIPAA breaches impact the U.S.?

In a way, the things you come up with during the brainstorming stage are like the raw data you started with, just not as empirical as your dataset. (But that’s what makes it fun!)


Now that you’ve collected all your raw data (brainstorming), it’s time to structure your talking points with an outline. You can play around with the order of your talking points; I sometimes go sequentially (1-2-3), consequentially (Insight A led to Insight B), or simply from more general to specific.

You can also phrase your talking points as questions; identifying which charts to include in your dashboard is easier this way. As you come up with your questions, take notes on what visualizations will show the insight best. In general, stick to showing one thing per chart; that “thing” (or piece of information) does not necessarily have to be the one insight, as an insight may contain two or more elements.

  • For example, one of my insights is that HIPAA breaches are on the rise.
  • What does “on the rise” mean? Well, I want to say that HIPAA breaches are increasing both in number of incidents and in number of people affected by breaches every year – this insight is composed of two different things, so I’ll probably want to include two visualizations for this insight.
  • If you have several interrelated talking points, packaging them under a few broader overarching questions will go a long way in facilitating your audience’s understanding, as the interrelated talking points will all reinforce the Big Idea.
  • The outline of my outline (or my pre-outline) looked like this:




HIPAA breaches are on the rise

How have HIPAA breaches impacted the U.S. over time?

Line chart for # of breaches

Bar chart for # of individuals affected by breaches by year

Impact of breaches on states varies greatly

How do HIPAA breaches impact states?

Maps for quantifying recent state impact in different ways

Hacking/IT incidents are the most common type of breach

What is the most common type of HIPAA breach over time?

Bar chart for # of breaches by type

Line chart for # of breaches by type (trends over time)

You may realize that you’ll need to make other visualizations that you hadn’t made during the exploration/analysis process. That’s okay! Audience comprehension, not data analyst comprehension, is the goal now – just make sure you’re not veering off-topic when you’re creating additional visualizations.

Now that you’ve gotten the meat of your outline down, let’s think about the introduction. How do you want to introduce the topic and the dataset to your audience? Also, dashboards don’t necessarily need a conclusion, but you may want to come up with one to tie your story together if you’re presenting it to an audience.

As a planner, I find that the more time I spend prepping my outline, the less work I have to do later. This is because I’ve worked out all the kinks when nothing was set in stone yet; I don’t have to come up with ways to resolve issues on the fly just as I’m finalizing everything else.

  • For example, my outline looked like this:

  • Introduction
  • What are HIPAA breaches, and why do they matter?
  • About the dataset

  • #1: How have HIPAA breaches impacted the U.S. over time?
  • # of breaches increases every year (line chart)
  • Daily rate goes from 1 to 2 breaches between 2018 and 2021
  • # of individuals affected by breaches increases every year (bar chart)
  • Answer: They’re on the rise

  • #2: How do HIPAA breaches impact states? (Really: How do we quantify recent state impact, for CA vs. FL vs. NY?) (maps)
  • # of breaches per state – California had the most and is also the most populous state
  • # of people affected by breaches – Florida had the most
  • Highest state population doesn’t necessarily lead to highest number of people affected by breaches
  • % of state affected by breaches – Florida had the highest % [of the three states]
  • CA and NY have similar %, but CA’s population is double NY’s

  • Median size of breach – Florida had the highest median
  • CA’s median is lower than the national median – why?
  • Answer: Depending on how you quantify state impact, Florida is hardest hit
  • Why isn’t CA as affected by breaches?
  • CA has own medical privacy laws on top of HIPAA

  • #3: What is the most common type of HIPAA breach over time?
  • Hacking/IT incidents are the most common type of breach (bar chart)
  • Hacking/IT incidents are increasing over time
  • Daily rate goes from .5 to 1.5 breaches from 2018 to 2021

  • Conclusion
  • With hacking/IT incidents and HIPAA breaches in general on the rise, the U.S. should use CA’s medical privacy laws as a guide for strengthening HIPAA


(I tend to work on stages 3 and 4, visualizing and storyboarding, at the same time because knowing for sure how many visualizations there are informs the dashboard layout, though I ordered visualizing before storyboarding because for Tableau, you have to create the visualizations on individual worksheets before putting them together on a dashboard.)

It’s time to create the actual charts, since you now know what charts you need! As you make the charts, start making formatting decisions, such as:

  • Color palette (keep simple)
  • Font sizes (make readable)
  • Numbers (you don’t need ALL of those decimal points)
  • Tooltips (What do you want the viewer to see when they hover over an element of your dashboard?)


Okay, now is the time to bring in Excalidraw (though I like drawing out the layout on paper first). I suggest dividing up your canvas into sections for each subtopic or talking point and designating specific places for your charts and text. Even if you don’t know where everything should go yet, carve out space for at least an introduction of the topic and/or dataset, each of the sections for the subtopics, and the dataset source. The latter won’t take up a lot of space, but these are all things that must be on the dashboard, and placing additional elements on the dashboard once you have the “musts” will be much easier.

(Note: Depending on the kind of dashboard you’re making, you may not need an introduction section.)

Regarding dashboard dimensions, I suggest selecting the Fixed size option and making the dashboard “scrollable,” in that the length of the dashboard is much longer than the width is wide.

Keep in mind that you don’t want your dashboard to be cluttered – negative space is your best friend! In addition to making sure the text is concise, another way to reduce the amount of text on your dashboard is to reserve some of it for hover text (blog entry on that in the future).

Your dashboard may not go according to plan, and that’s okay! I expect about 80% of my outline (for any project) to remain the same, as some things may change by the time you actually make the dashboard; the idea is to minimize deviations from the plan, while allowing for a little flexibility.

  • For example, my Excalidraw storyboard and Tableau dashboard aren’t identical because I simplified some sections after realizing they weren’t necessary for my story.

You may end up making different charts due to one of your focal points inspiring new questions. This may change the scope of your main question and derail your original objective if you aren’t always asking yourself how each element relates to the main topic.

As you create your storyboard, you may also want to start thinking about user interactivity, but only include enough for the story to be told. Take notes on the interactive elements you want to include, and plan to spend some time looking up how to incorporate them if you’re not sure how to do it.

  • For example, for the map section of my dashboard, I wanted to swap the maps out, so that you can see California getting lighter and lighter with every additional way to quantify state impact, as I felt that that was the best way to visually represent the effects of California’s medical privacy laws on preventing HIPAA breaches.


We’re almost at the finish line now! It’s time to put your dashboard together! Start with double-checking that you have all the visualizations you need because you should know by now, after looking at your data from so many different angles.

I learned this the hard way… Tableau’s blanks and containers do not work the same way – make sure you lay down all your containers first, then your blanks! That’s another reason for why storyboarding is so important; all of your charts and text will have designated positions, and from there you can extrapolate where to place your containers, which will keep everything in place.

After figuring out where the containers should go, I like to go section by section to lay down all the charts first, before thinking about the text boxes. Because you’ve done so much planning by this point, putting together the dashboard should be relatively painless (linking again for easy reference). I’m always asking myself this at every step of the process, but especially now: Does every single thing on the dashboard have at least one purpose?

And then… you’re done! Ta-da! Your dashboard is now complete! I’ll be back in the following weeks to talk more about some of things I did for my dashboard, like the chart swap for the map section, but for now, I hope you’re enjoying the holidays!

See you next year! (Sorry, that’s my favorite joke.)


  • Start simple, then get complicated. Figure out how to do the easiest thing first, then layer in the complexity, but only as it benefits your story.
  • It’s always easier to cut content than to add more. If you’re not sure something belongs in your dashboard/story, put it in and keep moving on. Once you’re done, take a look at it as a whole (or get another set of eyes).
  • How you understand the data =/= how the audience understands the data. By the time you get to the dashboard point, you’re only focusing on the latter.
  • Every element on the dashboard should be doing at least one thing relating back to the overarching topic. If you don’t need it, take it out.
  • Make a copy of the original dashboard to make changes to. I like to preserve old drafts of projects both to compare old and new and to keep a record of everything I did. Seeing the changes helps with inspiration, if nothing else.
  • Save often!!!

Fri 02 Jun 2023

Thu 01 Jun 2023

Thu 25 May 2023