- Identify the four levels of content in the 4x4 model.
- Explain why “story” is a critical element in any data visualization.
- List three ways in which designers often go wrong when creating a headline.
- Recall the meaning and purpose of KWYRWTS.
- Recognize three strategies for making effective text-based slides.
- Remember three strategies for making effective charts.
Skill Level Beginner
- [Voiceover] Welcome to Data Visualization For Data Analysts. I'm Bill Shander, founder of Beehive Media, an information design and data visualization consultancy in Boston. This course is intended to help data analysts, people who are neck deep in data all the time. You already know how to work with and think about and even visualize data, I bet. It's what you do everyday. But I'm gonna help you get beyond the data and think more clearly and strategically about how to present that data to an audience. We'll cover a bit about the primary challenges we face as communicators in today's world, and how to begin to think about solving them.
Then we'll go through ten primary lessons, the most important things to think about when visualizing data for your audience. So you're not simply kicking charts out of Excel, STATA, SAS or whatever tool you're using, but rather you're really delivering the best visualization to tell the story you're trying to tell. And I'll share some examples of redesigned visualizations I've done to make the theoretical more tangible. I hope you find the content fun and interesting and of course helpful, in your day to day data analysis practice.