The storytelling process and why it's important for data visualization

What is data visualization?


There are two types of data visualization: explanatory and exploratory. Explanatory visuals deliver specific aspects of the story to the audience, while exploratory visuals allow them to connect correlations, recognize trends, and draw their own conclusion.



What is data storytelling?


Data storytelling is the concept of creating a narrative using data and analytics that support the hypothesis of your story.


Data storytelling uses several types of data to craft a great story. To create a data story, you must first decide what you want your users to know.


Add value to your story, increase credibility, build trust, foster engagement, provide proprietary data, generate brand awareness, and position your organization as an industry leader.


Why are data visualization and data storytelling important?


To build a compelling story with data, you need to provide your hypothesis, reasoning, and data to back it up. Data visualizations can help, but they don't tell the whole story.


How data visualization and data storytelling work together


Data storytelling is the art of telling a story using data. Data visualization is the art of presenting data in an easy to understand format.


To craft a successful data story, you need to provide context, attention to details, critical insights, and a call-to-action. Data visualization helps you do this.


The differences between data visualization and data storytelling


Data storytelling is a tactic used to enhance your storytelling, while data visualization is a tool used to translate vast amounts of complex and valuable data into something people can more readily understand.


How data visualization and storytelling are similar


Data storytelling and data visualizations work together to build an engaging, factual, and contextual narrative.


Creating a data storytelling framework


To create a data story, you need to understand the context and results of your data analytics, and then use some best practices to create the framework.


Define your objectives, understand your audience, and incorporate key elements of analysis storytelling into your data story. To effectively communicate data through visualizations, you need to choose the right tool, follow graphic design best practices, and make an insightful and human story. Adding supporting, self-explanatory graphics to conceive a consistent storyline adds interest and increases engagement.


Data visualization and storytelling solutions


When deciding on a solution, make sure it can work with your critical business data from across the organization.

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