Introduction
Storytelling is an interactive art of using words and actions to create new worlds and experiences in a reader or listeners imagination.
Storytelling with data on the other hand is the concept of building a compelling narrative based on complex data and analytics to help you tell your story and influence and inform a particular audience. Data storytelling (data visualization) leverages visual attributes and cues such as charts, graphs, and maps to create an engaging, informative, and compelling data story.
To create a compelling data story requires you to understand the fundamentals of data visualization, and the principles of effective communication with data. Concepts which are well articulated in this book I recently came across “Storytelling with data”.
Storytelling with data, goes beyond the convectional tools to the root of your data, teaching you how create an engaging, informative, and compelling data story. “Helping you get rid of the ineffective charts, one 3D pie at a time”.
Some of the lessons you can learn from this book are.
1. Understanding the importance of context
Context is simply the information that helps viewers of your visualizations better understand what they’re looking at. Having right context will distinguish your visualization from being superficial to a genuine data presentation that motivates readers to take action.
2. Determining the appropriate type of charts and graphs
Charts and graphs are the building blocks of data visualization. Choosing the right chart and graph is key to conveying your data story in the most effective way. Depending with your data story, be it showing comparison, composition, correlation, distribution or location – this book helps you narrow down to the most appropriate chart types for your data.
3. Recognizing and eliminating clutter
A good analyst recognizes and eliminates all elements that distract users from understanding and interpreting data visualizations. This can be simple elements such as gridlines, excessive labels, unnecessary color variability, unnecessary axes and legends etc.
4. Directing your audience attention
Successful visualizations MUST grab user attention. From choosing the right charts - paired with the right visual attributes, and positioned on right area of your visualization depending on the importance of the metrics. Data experts can direct users to the most important metrics, communicate, and motivate users to take data driven-actions.
5. Thinking like a designer
Design thinking is simply a human-centered approach to creative problem solving that combines what is desirable to users and what is technologically feasible – to build appealing data products.
Conclusion
Data visualization is both an art and a science, while at it you’ve to strive to provide the right balance - while ensuring you provide the right data context, choose the right charts and graphs for your data, consider and direct your audience, while balancing your design choices to build data products that are free from clutter.
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