Data Visualization and Communication

Data Visualization and Communication

Data visualization transforms data into visual representations revealing patterns, trends, and insights. Visualization is both analytical tool and communication medium.

Principles

Tufte: maximise data-ink ratio, avoid chartjunk. Gestalt: proximity, similarity, closure. Choose chart types by data relationship: comparison, composition, distribution, relationship.

Chart Types

Bar/column (compare), line (trends), scatter (relationships), pie/donut (composition, sparingly), heatmaps (magnitude), geographic maps (spatial), box plots (distribution).

Interactive Visualization

Filtering, zooming, tooltips, drill-down. Tools: Tableau, Power BI, Plotly/Dash, D3.js. Interactive dashboards enable self-service analytics.

Dashboard Design

Clear purpose, key KPIs prominent, logical layout, consistent formatting, appropriate charts, actionable insights. Avoid clutter.

Storytelling with Data

Combine data, visuals, narrative. Structure: context (why), insights (what data shows), action (what to do). Cole Nussbaumer Knaflic's approach.

Reporting

Automated reports (regular), ad hoc analysis (specific questions), presentations (stakeholders). Jupyter (technical), PowerPoint (business), Tableau (interactive).

Summary

Data visualization and communication transform analysis into action through design principles, charts, dashboards, and storytelling.