Visual Design - Do not let Data be your cul-de-sac!
summary
Claims that 9 out of 10 companies get stuck in a “data dead end” because dashboards show insight but don’t lead to decisions, and prescribes a workflow: brief → sketch/iterate (uses Figma and whiteboarding) → prototype → build in BI. Recommends mapping precision to chart choice (position/length = bars/lines; area/color = treemap/map), avoid 3D and pie-on-map, use gray and color‑blind palettes (test with simulators), and apply the six Gestalt principles for clarity.
AI-written summary · about
chapters (15)
- 0:00Visual design importance
- 1:16Data dead ends
- 3:21Good vs bad visualizations
- 7:11Effective visualization criteria
- 7:57Purpose with three Ws
- 9:00Dashboard sketching
- 10:06Chart selection by precision
- 11:51Gestalt principles
- 12:57Proximity and similarity
- 16:05Enclosure and closure
- 19:14Continuity and connection
- 21:42Color in visualizations
- 23:06Color blind friendly dashboards
- 24:11Visual design for storytelling
- 24:54Closing and feedback
related talks
20mearn to make the point: data visualisation strategy
53mDashboards: interactive data visualization
43mYou Don't Need Data Storytelling If You Do Dashboards
20mLevel-Up Power BI Dashboard Storytelling with DataViz Tools
22mWhen Visualization Best Practices Fall On Deaf Ears
37mMaking Informed Decisions: Guidelines for Creating an Effective Dashboard
47mMastering Power BI Design with User-Centric Frameworks
50mDVUX: Data Visualization and User Experience
