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Data storytelling


Data storytelling is the process of translating data analyses into layman's terms in order to influence a business decision or action.

With the rise of digital transformation and emphasis on data-driven decisions, data storytelling has become a much-talked-about skill in the world of data science. The goal of data storytelling is to help line-of-business (LOB) decision makers connect the dots and understand the context and importance of the data that is being shared.

To be considered successful, a data story should:
  • Provide the audience with information in a way that is believable and easy to understand.
  • Allow the audience to quickly grasp and absorb the meaning of the data.
  • Inspire audience members to share the data story with others.
  • Encourage audience members to take action.




To date, there is no set of best practices on how to tell compelling data stories, but experts often describe data storytelling in traditional storytelling terms, which includes a "hook" that will capture the listener's attention, a narrative the listener is able to relate to personally, images that enhance the story and a conclusion that leaves the listener satisfied.

Typically, job openings for data storytellers require the following skills:
  • Ability to use data to structure a narrative.
  • Experience communicating a narrative through words and images to an audience.
  • Talent for boiling complex concepts into simple, relatable storylines.
  • Willingness to adjust the narrative to meet the needs of a particular audience.
  • Ability to select the right data visualization tools to translate the results of an analytics application.
  • Experience creating bar charts, line charts, sparklines, bullet graphs, scatter plots, treemaps, background mapping and infographics.
  • Hands-on experience with enterprise-level analytics software.
  • Familiarity with machine learning and predictive analytics.


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