Debunking Common Misconceptions About Data Storytelling
Data has grown in significance over the years. So much so that just about every aspect of our lives is influenced by how we analyze and understand data. Indeed, big data plays a role in just about every industry and can guide strategic decision making for business. Because data has become so critical, it’s equally important to understand and gain insights from data. And that’s where data storytelling comes into play. Through data storytelling, data can be more accessible and understood by the average person even if they lack data fluency and knowledge.
Because of how popular data storytelling has become, misinformation and misconceptions have proliferated, making it confusing to understand how best to leverage and utilize data storytelling. Since data can drive decision making and determine the course of a business, it’s critical to understand the limitations and myths of data storytelling. In this article we debunk three of the most common misconceptions around data storytelling, helping you better understand data as a whole.
Misconception #1: Every Form of Data Visualization Tells a Story
One common misconception around data storytelling is that all data visualizations tell a story, which can oversimplify data visualization as a whole. While it’s helpful to convert data into more understandable mediums such as graphs and charts, you also have to make sure that you’re communicating everything effectively and accurately. Charts or graphs that are littered with multiple data points can be confusing and may end up hurting your data storytelling efforts. Just because something is visual doesn’t mean it’s telling a story. For example, a pie chart showing sales numbers from the last year isn’t meaningful on its own, as it requires the viewer to parse out data points and reach their own conclusion. This can be just as difficult to understand as showing someone raw data. It’s important to pay close attention to how your data visualization tells a story, and that you provide context.
Misconception #2: Data Storytelling Is Solely About Visualization
While people understandably gravitate toward data visualization when telling a data story, there are other equally important elements. Alongside strong visualizations, you also need to seamlessly integrate narrative elements that will supplement the graphs and charts that you’ll be using. These elements can add related information to make it more useful, including helping a viewer identify patterns, trends, or relationships. To use the sales pie chart example again, giving your audience more information like the timeframe, previous benchmarks, and anomalies can all tell a more powerful story than just visualizations alone. This can be helpful in deciphering the data that’s being presented and give your audience more opportunities to engage with the data.
Misconception #3: Data are the Characters of the Story
Lastly, data should not be the main characters of the story. This doesn’t mean that data isn’t important but it’s only one part of the equation when it comes to data storytelling. It’s important to remember that data isn’t always the whole truth, it’s often a reflection of our socially constructed world. The reality is that data is capturing human activity or the results of this activity which means all the biases and assumptions of humans are part of the data. For example, the perspective of a historically marginalized group of people such as the homeless or people of color, may not be reflected in data collection. This doesn’t mean you can’t use data, it just means you have to be aware of and account for the ways in which data may not show the whole truth or reality.
Everything from data collection (decisions about “whose voice is heard”) to presentation (choices about what kind of chart to use, what colors to use, etc.) are made up of human choices that could influence someone’s understanding of what you’ve done. Every decision about collecting or presenting information makes it subjective and therefore, open to different interpretations. The total sum of the parts – not just data – is what makes up data storytelling and the insights gleaned from it.
Conclusion
When it comes to data storytelling, understanding what it isn’t is just as useful as understanding what it is. Thinking all visualizations tell a story, focusing only on data visualization, and thinking that data are the absolute truth, are just a few common misconceptions. While data can be invaluable in many ways, it’s important to keep these myths in mind to ensure you can leverage data storytelling in an accurate, practical, and helpful way.
If you want to understand what your data is telling you, schedule a call or start your free trial of Gemini Explore today! We can help solve your biggest data challenges, enabling you to understand and share data stories that drive your business forward. By connecting the dots between data from disparate sources, Gemini Data helps organizations effectively transform data into stories.
