Amy Balliett summarizes all that you should take away from this online course: tips on data visualization and major mistakes; the types of charts and graphs that are most effective in myriad situations; and how to make charts and graphs both visually appealing and easy to understand.
- [Amy] I hope you enjoyed this course on data visualization do's and dont's. From learning about data visualization mistakes to avoid to understanding when to use different types of charts and graphs and finally learning how to make the visually appealing. This course was designed to help grow your skills in one of the most in demand fields that exist today, data visualization. If you would like to learn more, check out my course on how to design infographics, which also includes a high-level recap of this course.
If you already feel accomplished in infographic design and would like to take things to the next level, consider my course, Visual Campaigns for Beginners, which breaks down how to run a visual campaign from beginning to end. And also, be sure to check out other courses, like Designing a Data Visualization with Bill Shander where you'll learn how to analyze and design big data sets. Or if you're just learning about communicating with visuals, I suggest checking on Von Glitschka's 5-Day Drawing Challenge: Communicating Through Drawing.
Thank you again for your time and hopefully now you feel confident creating quality data visualizations.
To succeed in design and marketing today, one must know how to interpret and properly visualize data. This course, developed and led by Killer Infographics CEO, Amy Balliett, walks you through the ins and outs of creating accurate and compelling data visualizations. Amy focuses on best practices, not tools, although she does provide an overview of Illustrator graphing features. Using these tips, you'll learn how to stand out from the crowd and create charts and graphs that combine precision with visual appeal.
- What charts and graphs work best for different types of data
- Putting data into visual and textual context to ensure it is accurate
- Visualizing data that doesn't lend itself to imagery
- Adding visual appeal without sacrificing accuracy
- Using the Adobe Illustrator graphing tools
- Avoiding common data viz mistakes