Data visualization best practices can transform the work of scientists and engineers
Eight Data Visualization Myths
“If you’re creating charts that people are going to be making multimillion-dollar decisions on – or possibly life or death decisions on – then you have to have some training,” says Nick Desbarats, a data visualization and dashboard design educator. What are the consequences of bad charts and graphs? You may misrepresent reality or fail to surface key insights. Or your audience won't even look at your data visualization because it requires too much cognitive effort. In this presentation, Desbarats dispels eight common myths about data visualization.
Watch to learn more about:
- Obviously – and unobviously – bad chart designs.
- How we should – and shouldn’t – evaluate the effectiveness of a chart.
- Shifting our thinking about charts from what they are to what they are for.
- Brain science and how our design choices subtly influence how people perceive data.
- The skills you need to make great data visualizations.
Insights from experts at W.L. Gore and SAS on how to gain momentum for your ideas and inform strategic decision making
Good visual design is as important as good grammar. Understanding data visualization best practices can help you communicate about data in an accessible, influential way. When designing graphs for others, you must carefully construct them so that audiences can consume the information with ease.
In this discussion, data visualization experts share how to improve graphicacy and data savvy at engineering and science organizations, how to make charts accessible for various audiences and how to use graphs for data exploration.
You’ll hear from:
- Nick Desbarats, Independent Data Visualization and Dashboard Design Educator, Practical Reporting
- Chris Chen, Enterprise Analytics Champion, W.L. Gore
- Xan Gregg, JMP Director of R&D, SAS