earn to make the point: data visualisation strategy
summary
Defines four types: storytelling, status, analytical, exploratory and shows when each actually moves decisions: flow diagrams that label endpoints to prove architectural changes, dashboards of 5–9 graphs that let engineers spot anomalies in ~5 seconds, infographics that replace long docs, and interactive explorative builds (example: Treejack) that let researchers find where users get lost. Recommends concrete tools — d3.js for bespoke explorers, c3 for simple charts — and stresses prototypes and user testing so the visuals work.
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chapters (10)
- 0:00Start
- 3:12use data visualizations as a visual communication tool for your work
- 6:15become an expert box drawer
- 7:46inputs and the outputs use simple supporting graphs
- 8:02visualizing these metrics alongside of your diagram
- 9:45avoid the whole dashboard feeling overwhelming
- 10:17create dashboards through drag-and-drop
- 12:30communicate all of the other responsibilities
- 12:59guide the reader from the start to the end of our story
- 17:20create beautiful data visualizations
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