Data Visualization is a Must-Learn Skill Today. Here's Why.
May 9, 2019
According to LinkedIn Learning research, new graduates – defined as people six months out of college or less – disproportionately learn data visualization. While this speaks to an immediate need new graduates face, mastering this skill early will give new graduates a huge edge in the workforce.
Because today, data visualization is becoming an absolute must-learn skill. As all organizations become increasingly data-driven, the ability to work with data isn’t a bonus, it’s essential.
To learn more about this topic, we interviewed Bill Shander, LinkedIn Learning Instructor and one of the preeminent experts on data visualization. Here’s what he had to say:
What is data visualization and why is it so important?
Shander: Few terms are so easily defined as data visualization. It literally just means a visual representation of data. Now, when we hear “dataviz”, we generally think of charts and graphs. And those certainly make up the bulk of our experience with dataviz, but it goes way beyond that.
For instance, when someone asks a group of people to raise their hands if they love hip hop (which is pretty popular, according to the predictive Google search text I saw when looking for examples!), that’s data visualization! It is easy to see the visual representation of how many people love to hip hop by all those hands! Or when Hans Rosling explained population growth using plastic bins and a few illustrative props… that’s data visualization too!
Why is it important? Think about the Hans Rosling example. Population growth and demographics shifts are critically important to the survival of our species and the health of our planet. And it’s immensely complex. But a few plastic bins and some props make the data crystal clear. Tables of numbers couldn’t have communicated this information with even remotely the same power.
How can learning data visualization make you better at your job?
Shander: Business is data-driven. Full stop.
Whether you’re in sales and need to convince a prospect to buy your products or a manager trying to optimize employee performance or in operations managing manufacturing efficiencies – or really just about anyone doing just about any job – everything is measurable and can be scored against different KPIs (key performance indicators.)
This reality means we’re swimming in data and decisions that need to be driven by that data. Therefore we need to be constantly looking at, interpreting and sharing data with our colleagues, managers and customers.
Being skilled in data visualization will make you better able to understand what is happening in and to your company, explain this to your various stakeholders and maybe even persuade them to make the right decisions for the good of the organization. Data visualization is, IMHO, one of the most important skills for the modern-day workforce.
Why is data visualization important for new grads to learn?
Shander: Dataviz is important for everyone. But new graduates have an opportunity to leapfrog their competition by focusing on this skill.
First of all, this is something that is not widely taught in school, so you will set yourself apart if you have decent skills in this area.
Perhaps more importantly, data visualization is a really interesting blend of skills that, if you work to improve all four, you will be a rock star without any competition at all. If you can analyze data, communicate ideas effectively, have creative skills so you can create beautiful and compelling visuals of that data and you have the technical skills to pull it off – I describe people with all four as dataviz unicorns – you will be in very high demand.
And, by the way, you will have four extremely valuable skills to bring to literally any role. These are four skill areas that will be worthwhile no matter where you work and what you do! But you don’t have to be a unicorn to succeed. If you’re good at two or three of these skills, you’ll be better off than most!
What are 3-4 tips for professionals who want to better visualize and storytell with data?
Shander: I have a thousand tips. But if I have to limit myself to four, they are:
- You need to know what you are trying to communicate about your data. This is so obvious and yet it’s where people fail the most. Most people get data, and they immediately think “what chart does this data fit into” instead of “who am I talking to, what do they need to understand about this data, and what do I want them to do with that information?”. If you pause and think critically about this, everything you create will be better.
- You really do need to tell stories. Think again about that Hans Rosling video. Seriously, if you haven’t watched it, watch it now. I’ll wait… OK. That is so powerful and effective not just because of the visuals but because of the story Dr. Rosling tells. You need to organize your thoughts into a logical flowing sequence of information and put together a visual presentation that supports the story. The story comes first. Data is just an ingredient in the story.
- When it comes to creating visuals, remember that you are trying to trigger a specific response in your audience. And that response is all about allowing them to see what’s interesting about the data – patterns, outliers, trends, comparisons, etc. The way to do this is to eliminate everything from your visuals that don’t support this. Use as little labeling as possible, reduce the contrast of unimportant chart elements like axis labels and lines, reduce the colors of everything in the chart to be minimal, simple, gray. And then add back in color (as little as possible) and labels to draw the eye only to what’s important. I summarize this advice about design into two words: “Do less."
- Use your words. Say I can’t figure out what visual to use, or even what data to share, I will write out my entire story. I’ll write the version I might share with the audience (well-written, concise and edited) and a version that’s just for me (extremely detailed, maybe even full of run-on sentences.) That second story (my internal version) will usually tell me exactly what to do next – what detail to include, what visuals to create, how to bring the project home. This is a special trouble-shooting trick that never fails.
- Learning Data Visualization
- Picking the Right Chart for Your Data
- Data Visualization: Storytelling
- Data Visualization for Data Analysts
- Data Visualization, Storytelling, and Information Design: A Lesson and Listen Series