So, you have all of this data. All of these predictions that you have curated from your work. But now what? What comes after working with the computer science and statistical aspect of data science? Storytelling, of course! To some, it may seem obvious, but the communication of data science can sometimes be overlooked.
Instead of simply showing your data, make a story with it. Using storytelling and compelling communication can make your findings much more impactful. Also, depending on the context with who you are sharing your data, data scientists will need to be able to put their findings in simple and understandable terms. Aspects of said communication could include background on the reasoning behind why you started processing data in the first place. In addition, the results of your data and how you want to implement your findings into your organization.
Whether you are delivering your information through verbal presentations or written reports, some things could improve your storytelling techniques. As I briefly mentioned above, you will need to start by giving context that provides your listeners with some idea of why what you are saying is relevant. If your listeners do not know why they should care, they will not. Next, when discussing the data and your findings, you should be using creative and compelling techniques to convey your story. That could be by using images, graphs, charts, or videos to keep your audience engaged while simultaneously getting your point across. Lastly, wrap it all up by summarizing your work with the highlights of your findings. Leave your
audience with the most valuable aspects of your presentation.
All in all, communicating your findings as a data scientist can make all your work worthwhile. In my opinion, making your results easy to understand is an essential aspect of delivering data science. Also, emphasizing how your conclusions based on your data can improve your organization can give meaning to your work.
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