I didn’t understand the point of treemaps until I worked with a large structured dataset.
As part of an extensive user research effort, we collected open-ended survey data from 130 participants. After standardizing the data and doing thematic analysis, the next topic was to try and figure out a way to visualize it.
After analyzing the data, it was a dataset with over 20 themes and several different categories of respondents. This was a much larger dataset than I was used to visualizing: what was I supposed to do?
That’s when I first started to learn about treemaps. To understand…
Sometimes, the data doesn’t exactly work the way you want it to.
When working with data, you might run into a fairly common problem: some values make it hard to fit everything on one graph;
I just wrote my first book in a year after failing to do so for decades.
I’ve been writing since I was a child but never quite figured out how to complete a book: the number of half-finished novels and short story anthologies that I’ve created could probably fill a bookshelf.
Sometimes it was an issue of motivation, but usually, it was an issue of organization.
Halfway through a story, I would find that my character’s motivations completely changed or that I had no idea to tie it together. …
What should the scope of your Data Visualization project be? That’s something that I’ve been encountering as I’ve begun creating visualizations for work.
Learning Data Visualization from the lens of multiple fields has given me a unique perspective on applying it in my work life. But unlike courses, sometimes the real world isn’t clear with the scale and scope of what needs to get done.
There have been times where I’ve wanted to create a grandiose visualization, only to have to scale it back as I don’t have time for it. …
Thinking like a journalist helped me turn my user research into a 1-page summary. It’s always a hard process, condensing your user research into a 60-minute presentation. We can put much hard work into gathering key points that you might not present to your stakeholders. But a 1-page summary was an order of magnitude harder: my first draft was a mess, and I had no idea how many points I could support or what story to tell.
This is where the Journalistic approach helped me: I was able to sleuth several possible data stories to write about and find a…
My usability testing process has gained a new layer of depth from learning Data Science, with only a few minor changes. Over a year, I’ve made changes to the way that I’ve approached usability testing and been able to add quantitative elements to my analysis. But I hadn’t thought about the ways that I’ve changed until I found myself in the middle of another week of testing.
Here’s how my process changed.
Honestly, many of the underlying factors haven’t changed that much: I’m still seeking out feedback anywhere from 5–10 users who are subject matter experts (SMEs) who will be…
One of the quickest ways to improve your presentation skills is through storytelling.
Whether it’s persuading them to approve a new plan or persuading them to pay attention to a particular problem, most presentations are created with that in mind.
And one of the easiest persuasion methods is telling a story: they easily engage the audience, and they’re easy to remember.
However, if we’re going to take a story-based approach to presentation, we need to understand how to use one of its’ most important elements: the…
There tends only to be one way of thinking about chart choosers: based on the data.
There is a very famous chart chooser done by Dr. Andrew Abela that has traditionally been how you choose which chart to use.
I got an unexpected crash course in KPIs when I was learning about Data Visualization. Like many UX Designers starting, I knew next to nothing about them initially: the extent of my knowledge was that KPI stood for Key Performance Indicators, and they had something to do with the business. But when I started to adopt a more scientific mindset towards design, specifically about hypothesis statements, I learned more about the importance of metrics. Part of this was understanding how using KPIs with my design recommendations would usually result in more productive meetings with the rest of my team.
As UX professionals, you’re well-equipped to improve bad visualizations.
That’s the fact that I hadn’t realized until I was doing a #MakeoverMonday project.
Bad visualizations tend to have two leading causes: bad data stories and visual clutter.
But while we may be a little unfamiliar with the former, we often spend a lot of time thinking about the latter.
We spend a lot of time thinking about the best method of organizing the elements on the page to create a great user experience: those same skills can also help when trying to declutter a visualization.
But while we may notice…