The Value of Mastering Data Visualization & Storytelling for Data Scientists
All of the analysis you perform and the insights you generate as a data scientist would not be worth your time if it weren’t for storytelling and visualization. Simply presenting numbers and data from your analysis rarely helps accomplish anything for you. The people you are reporting to have numerous questions that can only be answered through in-depth data visualization and storytelling.
Imagine a weather forecaster walking in to tell people about an approaching blizzard. Their warning won’t have any impact on the audience if they don’t use appropriate visuals and storytelling techniques. Hence, forecasters use graphics and interactive methods to keep viewers hooked and informed.
Both visualization and storytelling techniques help data scientists communicate the insights they have achieved after their analysis. These analyses and insights are meant to help improve decision making for everyone involved.
“The ways in which organizations deliver business analytics insights are evolving, notably in the rising use of what is called data storytelling,” states James Richardson, Senior Director Analyst at Gartner.
Data scientists need to realize that not everyone in the organization they work for will be able to understand data and analytics in a manner that they do. Hence, they have to apply visualization and storytelling techniques that can actually serve the purpose here.
Many organizations have realized the importance of data visualization and are investing in implementing it. However, they are still facing challenges in representing data in a manner that can genuinely optimize business value.
The lack of storytelling and visualization in a data presentation can actually slow down the process of data scientists, leading to a reduction in the quality of research being done as well.
Storytelling is just as much a part of a data scientist’s job as any other technical aspect. Gartner has described storytelling as being a non-technical trend that is extremely critical to the success of a data science program.
Whenever you are presenting data in front of an audience, you need to gather and offer context to them. Context is what builds value that surrounds insights generated through data. Through their storytelling skills, data scientists can help build significant context and can effectively explain their ideas to everyone present.
A good storytelling narrative can help make data and analytics a lot more accessible. Storytelling has been part of marketing for a long, long time and has served a significant purpose. A good storyteller isn’t just meant to evoke emotions and responses from the audience, but also wishes the audience to learn and comprehend what is being displayed or presented. As a data scientist, you are serving the latter purpose more than the former one. You want your audience to understand the significance of what you are presenting. You want them to learn from the insights and make informed business decisions based on them.
The insights generated from the analysis are quite strategic for the organization running the data science campaign. You need to gather and convey your data in a reasonable manner as it is these insights that usually make or break the deal for a sound data strategy. Many important and strategic business decisions could be hanging on a thread, waiting on the insights from analysis.
Storytelling is, at its core, an extension of business intelligence, as it combines the visualization of data with a powerful narrative for pushing your point forward. Data scientists and CDO’s can utilize storytelling as a non-technical data science tool to share a powerful data vision, generating calls to action and influencing decision making.
