Everywhere we look today, we find data.
With data being generated in every aspects of our lives, we have seen a rise in data storytelling. From politicians to YouTube stars, everyone is using data to share compelling stories.
So, what is data storytelling? According to the Economist, it is “melding the skills of computer science, statistics, artistic design and storytelling.”
Creating a captivating narrative with data requires skills beyond technical expertise. Here are 5 actionable steps to get started with your data storytelling.
Before you dive into your datasets to find meaningful information, find a story that you want to share.
Oftentimes, people with access to several datasets will run endless analyses and generate fancy statistical reports. Remember, for data storytelling, readers want a story not a statistical report.
So, the first stage of data storytelling is to start with a story. Find the purpose of your story. Who are you writing the story for? Then find data that will support your story.
What if you don’t have access to any data?
Do research to find a reputable data source.
Data sources can include government agencies, non-profit organizations, hospitals, private companies, or universities. Many government agencies make data available for public use. Here are some examples of publically available databases:
Now that you have the data, what do you do?
There are two specific issues you need to address before processing data:
Converting “raw” data into a usable format can be a bottleneck in your workflow. However, it is also one of the most important steps in extracting your data.
After making sure your data is in a usable format, you need to streamline your data. What does it mean to streamline data? For example, a dataset can contain hundreds of variables – an attribute that describes a place, person, or thing. However, you may only need a handful of variables for your story. Only include data that is relevant to your story and leave out unnecessary information.
In any type of storytelling, it is crucial to provide contextual information. Who is the story about? When and where did the story take place?
Every data story should tell us where the data was collected and during what time period. The story should also include information about the players in the data. Try to be specific and detailed when providing contextual information.
You have finally arrived at the exciting part!
You get to choose how you want to tell your story. Do you want to create a diagram, write an article, or create a video?
It is a key decision in your data storytelling process. Don’t underestimate the power of narrative style as it can either attract or deter readers away from your story.
But what are some narrative styles in data storytelling?
In their pivotal work in data narrative, Edward Segel and Jeffrey Heer describe seven genres of narrative visualization: 1) magazine style, 2) annotated chart, 3) partitioned poster, 4) flow chart, 5) comic strip, 6) slide show, and 7) film/video/animation.
With all these steps in place, you are ready to start your data storytelling journey.