Data storytelling allows you to derive meaning from a specific dataset and convey it to the audience with the help of visualizations and narratives. The technique includes data insights and communicates messages to your audience. There are three vital components included in data storytelling, all of which are core parts of data storytelling training.
Complete data can serve as the best foundation of any data driven storytelling when analyzed accurately and adequately. To analyze data, you can use diagnostic, prescriptive, descriptive, and predictive analysis techniques. It’ll help you to comprehend the entire picture. Next, a narrative is required. A written and verbal narrative, otherwise known as a storyline, can be used to share ideas gathered from data. These are powerful data storytelling examples.
Next, it’ll be used to contexts related to it along with the actions you suggest to keep your audience encouraged. Besides, visualizations are the third important part of data storytelling. Visual representations gathered from the narrative and data can be used to communicate the story concisely, clearly, and in a worth-remembering manner. The visualizations can vary from charts, videos, pictures, diagrams, and graphs.
Data storytelling is useful when communication is done via internal mediums. For example, user data can be used to enhance a product’s utility. Next, it can be done via external mediums- for example, creating a propelling case that’ll help allure potential customers to buy your product. The narrative elements used by data storytelling are similar to that of normal storytelling- it involves conflict, resolution, characters, and setting.
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