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How a classic story arc can be used for analytical data stories

The classic story arc is a narrative structure that has been used for centuries in literature, film and other forms of storytelling. It consists of several key elements that help to create a cohesive and compelling story.

However, the traditional story structure can also be used when sharing data stories. Although these are highly factual and analytical, a data story still follows the same kind of arc or trajectory as a typical story.

Historically, the anatomy of a story typically included the following stages -


The exposition is the beginning of the story where the background information is provided and the setting, characters, and their situation are introduced. This is the part of the story where the reader or audience is given a sense of what the story is about, who the characters are, and what the setting is like.

It serves several important functions in a story and establishes the context: The exposition provides the reader or audience with the necessary information to understand the story and the world or environment in which it takes place.

Rising Action

Rising action is an important stage for building tension and suspense. It is where the audience starts to feel invested in the story and the characters and should be intriguing enough to keep the audience engaged.

As the characters begin to face challenges and obstacles, they will develop and change throughout the rising action. They may start to realize the true nature of the problem and the sacrifices they will have to make to solve it. This is the stage where the audience becomes invested in the eventual outcome of the story.


This is the turning point of the story, where the conflict reaches a peak and the outcome is decided. This is the most dramatic and intense part of the story that builds to a crescendo and sweeps the reader along with it.

It often involves a highly charged confrontation between characters, usually the hero and the villain, and it is the point in the story where the main characters achieve or fail to meet their goal.

Falling Action

Here is where the previously built peak of tension breaks as the story starts to resolve. Everything that occurs after the story’s climax is part of falling action. Loose ends are tied up, things are explained, issues are resolved and the story starts to draw to its conclusion.


Known officially as ‘denouement’, the resolution is the conclusion of the story, where the conflict is resolved, and the characters find closure. It ties the narrative together and connects the plot together as the story concludes.

How are classic stories related to data stories?

Now we understand the progression of a classic story arc and each of the stages contained within -

Exposition > Rising action > Climax > Falling action > Resolution

It is possible to relate the storytelling format to the practice of formulating and telling data stories. In the context of these modern-day technical "data stories" , the typical terms for each stage of the story are not used, however the same principles apply.

A well-constructed data story is expected to provide the information that is needed to understand the problem or question that is being asked. Data stories are narratives in much the same way as classic stories except they use data, visualization, and other forms of analysis instead of words to communicate insights and information.

These storytelling tools are used by analysts to extract, manipulate, and make sense of complex data sets and communicate findings and insights in a clear and engaging way. Data stories can be helpful for uncovering information and finding solutions in a variety of fields such as business, finance, science, or journalism, and they can be used to inform decision-making for key strategies.

Information presented in this way can be used to find data-driven solutions, or simply to present data in new and compelling ways to derive clear insights or uncover hidden facts. Data stories can take many different forms, such as reports, dashboards, infographics, presentations, and interactive visualizations. They may be used to convey different types of information, such as quantitative data, qualitative data, or a combination of both.

A data story typically consists of the following elements:

  • A problem or question that requires an answer

  • Data used to answer the problem or question

  • Analysis process to identify patterns and gain insights

  • Visualization and other forms of data representation to present findings

  • Narrative and context that gives explanations and interpretations, and shares recommendations for solutions.

Visualizing the story

The goal of a data story is to make data more accessible and actionable, to help people make sense of it, provide insights that can be used to drive decisions. One key aspect of data storytelling is the ability to visualize data. By converting it into an easy-to-interpret format by using charts, graphs, and other forms of visualization, the storyteller can make the insights more accessible and engaging to the audience.

In the same way as a traditional, written story follows an arc, data stores also possess a similar cadence.

  • Data extraction and collection is similar to the ‘exposition’ part of storytelling where background information is acquired and problems are introduced.

  • The data analysis is usually the ‘rising action’ where the analytical process is used to identify patterns and insights within the dataset.

  • The ‘climax’ of the data story is the point where the data-driven solution is found or a conclusion has been effectively reached.

  • As solutions are determined and the remaining points addressed, this is closely related to ‘falling action’ in the story arc. It may go into detail about how the solution was implemented and how it was received.

  • The ‘resolution’ of the data story is where the data story concludes. Wrapping up all key points and providing a summary of the findings and insights.

In conclusion

While it is true that not all stories or data stories will contain all of the story elements presented in the exact same way each time, many of them may be combined or re-purposed in different ways, depending on the goal and context of the story being told. There will a beginning and an end and a clear progression of points that lead the reader or the viewer through each of the individual story stages.

Both methods of telling classic and data stories use background information to introduce a problem, create a scenario, and present information. Each builds the story and presents details that highlight a main point. Then follows it through to the findings with any implications towards the final resolution, and future steps.


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