Using Data Visualization to Tell Developer Stories
Data visualization can enhance stories that directly connect with your audiences and developer communities.
Data is everywhere. We are flooded with it every day, whether through our phones or our televisions or even just taking a walk down the street. But what can we do with all of this data? Well, we can craft stories for a particular class of audience.
…a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it. — Herbert Simon
Data visualization is one way to make sense of information and create compelling stories with it. Developers are predisposed of making sense of information and diving into the data shaping the patterns.
What better way to connect with your developer community than to presenting data visualizations!
What is data visualization and why do it?
Data visualization is a way to turn data into a visual representation. When you look at a chart, graph or table, you’re seeing data in visual form.
Data visualization is also a powerful tool for quickly and easily communicating complex information to a wide audience.
It’s a great way to communicate data to people who don’t have the time or resources to spend hours researching an issue or learning about something new. For example, you can use data visualizations in presentations, reports and infographics — or even just on social media platforms like Twitter or LinkedIn.
Data visualization can be used in many ways: to explore trends and identify patterns; help people understand complex concepts; and make decisions based on the information presented.
Empirical research studies have shown that visual formats are more effective than text formats when it comes to communicating information because they have the power to capture attention, engage readers and even improve retention rates.
Spin narratives with data visualization
Visualizations can help us understand trends and patterns, identify what’s working (or not) and make decisions based on the information presented.
Static data visualizations are static images that contain a single set of data points that can be viewed by anyone at any time. This is similar to a table or chart you might see in an budget or formal report.
Interactive data visualizations are more interactive and dynamic. They allow the viewer to interact with the data in some way, such as by clicking on a specific point or filtering through different variables. This allows you to see how your audience interacts with it and improve it based on their feedback.
Data visualization is not only used to make comparisons, to explore or to explain, it can be extended as a way to tell a story about the past, present or future.
Data visualization can tell stories about the past, present and future.
The way I like to think of it is that data visualization should be used as a tool not only spinning a narrative, but also give another dimension for explaining factors driving a phenomenon but also the outcomes.
But if you want your audience to feel something, then make sure they have some sort of hero journey that they’re going through as they read through your data visualizations. Of course, for developer stories, the hero is the developer.
The best data visualizations have a clear story arc that you can follow and understand. If you want your audience to feel something, then make sure they have some sort of hero journey that moves from struggle to resolution. This also means that it’s important to keep track of what kind of data that is being presented in each section — this will help ensure that there is a clear storyline throughout the entire piece.
Make sure you choose a theme for your visual storytelling, such as presenting the data in chronological order or grouping similar elements together.
Quick tips on good data design
The first step to creating a good data visualization is determining what you want to show. Before you even think about the design, it’s important to know what kind of data you’re working with, who your audience is and why they are looking at it. After that, consider these tips for creating a great visualization:
- Experiment with different types of visualizations that match the story, the goal you want to achieve and emotion you want to evoke.
- Test out and apply color to highlight important points in the chart or graph
- Employ motion to draw attention to specific points. Motion can be used to highlight an important statistic or as an eye-catching intro for your presentation.
- Keep everything consistent so users know what they’re looking at (for example, use the same colors throughout or make sure there’s enough contrast between text and background)
- Label any axes and add titles so users understand what all their numbers mean
- Make sure your data is accurate; if not, fix it before sharing
This is by far only a fraction of tips. To explore more, you can visit the site Data Journalism which dives deeper on best practices, techniques, and data visualization trends.
Study the from the best
Information is Beautiful
Information is Beautiful is a blog by David McCandless and has been featured in many popular publications. The website focuses on data visualization and how it can be used to convey information in a clear way. The site also has an online store where you can purchase posters, books, and other items based on their infographics. The site is updated frequently and always has new data visualizations to share. If you’re interested in learning more about how data can be used in your own work, this is a great place to start.
Flowing Data
The site Flowing Data is a great data visualization blog. The site was created by Nathan Yau, who is a statistician and data journalist. He has been featured in many popular publications and his work has appeared on the front page of The New York Times. The blog focuses on how data can be used to present information in a clear way. It’s updated frequently and always has new posts to share with readers.
New York Times, WSJ and WaPo
Publications like the New York Times, Wall Street Journal and Washington Post have a strong track record for great data visualizations to tell news stories from a different data perspective. All these large media publishers have a team of dedicated data journalists who use data visualizations to tell stories. These are a great place to get started with learning how to create your own data visualizations and should be a part of any student’s reading list.
The site also has a section where you can find resources to create your own infographics. If you’re interested in data visualization, this is a great place to start.
Tuning and sharing
Once you’ve built the visualization, you want to make it easy for people to find and share your work. The best way to do this is by making your data visualization interactive. You want users to be able to explore the data themselves and interact with it. Try adding things like charts that change based on user input or maps where they can pan around at will.
Make sure that any code or scripts necessary to run the visualization are available online so anyone who wants can see how it works before using it in their own projects.
If you want to share your data visualization with the world, the best way is to post it online. There are plenty of websites that offer free hosting for data visualizations, including Google Drive and Plotly. You can also just upload it somewhere like Dropbox or Github if you don’t mind people downloading your code instead of using a web-based interface.
Don’t forget that you can also make your data visualization interactive by asking questions. This can be done by using a survey or poll, but it could also mean asking people to submit their own data as part of the visualization. For example, if you were making an interactive map of crime rates in a city, you could ask people how safe they felt in certain areas.
Tell a story in an interesting way.
Data visualization is another useful tool to help you tell stories. It’s not just for the data scientists, but it can also be used to tell stories that are not just about data. You can use this technique to explain complex ideas and processes in a way that’s more engaging and comprehensible than only writing out the steps in text form.
When creating visualizations, decide who will be consuming them and what their level of knowledge might be before starting. If you’re trying to convey something basic like how many software developers there are in your company compared with five years ago or which technologies people are using most often, then stick with simple charts and graphs without too much detail — this information should be easy enough for anyone who works at your company to understand (or read).
On the other hand if you want everyone involved in product development from developers themselves through designers all the way up top management teams (which could mean non-technical people who aren’t familiar with code), then using more advanced techniques such as machine learning algorithms will probably be necessary since these might require some explanation beforehand so they’re better understood by those unfamiliar with technical jargon like regression analysis methods.
Overall, data viz is can be another way to tell a story that not only relevant and impactful because it’s the story data-driven and expressed using a quantitatively lens that developers will recognize and connect with.
It can inspire them to try something new, give them a reason to use your tool over another and ultimately help them get work done faster. With data visualization, you can create compelling stories in an interesting way that will keep people engaged until the end.
How do you want to employ data visualization into your developer relations and developer marketing programs?
I’m passionate about helping people build great and innovative products. We’ve taken on the communication challenges of startups, entrepreneurs, B2B software companies and organizations working with university researchers. Visit us at signetscience.com to learn more.
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