Choose Your Level
Pick the difficulty that matches where you are. You can come back and try a harder level later.
Choose the Right Chart
Given 5 different datasets, pick the correct chart type and explain why the alternatives are wrong.
The One-Chart Dashboard
Design the single chart you would put on a CEO's weekly email.
Build a Dashboard Narrative
Design a 4-chart executive dashboard where every chart answers a specific stakeholder question.
Exploratory Data Visualization & Chart Selection
Data visualization transforms numbers into visual insights. Employers seek analysts who understand visualization principles: choosing appropriate chart types (line, bar, scatter, heatmap), configuring accessible color palettes, and avoiding misleading axes.
1. Exploratory Data Visualization Deck
Portfolio presentation showcasing chart visualisations paired with analytical commentary.
2. Custom Chart Code / BI Dashboard
Clean Matplotlib/Seaborn/Plotly Python scripts or interactive BI visual charts.
3. Visualization Principles Audit
Self-audit evaluating chart contrast ratios, axis scale integrity, and visual legibility.
Frequently Asked Questions (Data Visualisation)
When should you use a line chart versus a bar chart?
Line charts are designed for continuous time-series trends over time, whereas bar charts are optimal for comparing discrete categorical groups.
Why should bar chart Y-axes always start at zero?
Truncating the Y-axis on bar charts exaggerates relative size differences between categories, misleading stakeholders about true proportions.
How do you ensure data visualisations are colorblind accessible?
Use colorblind-safe palettes (like Viridis or Okabe-Ito) and avoid relying solely on red/green contrast to convey status.
Explore Data Analytics Career Paths
Build proof of work across other topics or view full career roadmaps mapping technical skills to hiring expectations.