- In this course, I've shown you the importance of telling great data design stories. We started with the description of the key elements of a story. Then you saw how to weave context, plot, and conflict into the stories you share with your organization. Finally, you saw how to use these stories to motivate your audience to take some action. Telling better stories is a key part of being an effective data science team and delivering value to your organization. You can see more examples and in-depth information in my book, Data Science, Create Teams That Ask the Right Questions and Deliver Real Value.
It's available through A Press Publishing and in most online bookstores. This course is one of several available in the video library. A good follow-up to this course is Data Visualization Storytelling Essentials, by Bill Shander. He goes further into the details of which visuals work best for each story. His course is a great resource for finding the best data visualization while keeping it clear and interesting. I hope you enjoyed this course on Storytelling With Data Science.
Feel free to follow me on Linked In. There you'll see more examples of visualizations and strategies that you might try with your data science team. Thank you for watching and good luck with your career.
- List the five threads your team should focus on when spinning a yarn.
- Explain the benefits of using scenarios as story helpers.
- Explore how using conflict in a story can captivate your audience.
- Determine how details will enhance a story and make it memorable.
- Recall the downfalls of using too many visualizations.
- Define vision in the context of data-science storytelling.
- Recognize the features of good storytelling.