Dos and Don’ts of Data Visualisation

Whether on purpose or not, a statistician can mislead an audience with a chart. This article explains some chart design principles and common mistakes novice data analysts make. Think about the statistical charts you have seen on billboards, in the news, and in research studies. Using these principles as a guide, would you classify any of those charts as misleading? Be sure to take note of the suggestions for successful dashboards.

Dashboard

10 best practices for building effective dashboards

  1. Know your audience: modulate the complexity against your audience's level of expertise.
  2. Consider display size: consider the way your audience is going to consume your data. When designing for mobile, reduce the amount of interactivity. Stack content vertically for phone screens.
  3. Plan for fast load times: for optimisation tips, read here.
  4. Leverage the sweet spot: consider how your audience will 'read' your dashboard. Use the design (lines, white space, colours) to create a structure and guide the flow.
  5. Limit the number of views and colours: stick to two or three views in order not to overwhelm the reader. In case you need more, add other dashboards or use a story. Reduce the number of colours and use them intentionally.
  6. Add interactivity to encourage exploration: add filters and a search box, and highlight actions.
  7. Format from largest to smallest: from a formatting perspective, the hierarchy of a dashboard looks like this: 1. Theme; 2. Workbook; 3. Worksheet.
  8. Refining your dashboard: Tooltips are a useful way to reinforce the story. Remember to customise them and format accurately. The Viz in Tooltip feature augments your dashboards and stories with relevant data without introducing more clutter.
  9. Eliminate clutter: every element should serve a purpose: reduce the number of colours, lines and legends, and the amount of text if not necessary.
  10. Test your dashboard for usability.