Data Visualisation, Dashboards & Data Storytelling is a structured track of 14 lessons that build a complete, interview-ready understanding of the topic. Work through them in order, then use the quiz and flashcards in each lesson to revise.
What this course covers
- How People Read Charts: Visual Encoding & Perception - Which visual encodings the eye judges accurately, ranked, with the implication for design.
- Choosing the Right Chart for the Question - A mapping from question type - comparison, composition, distribution, relationship, trend - to chart.
- Charts That Mislead: Truncated Axes, Dual Axes & Bad Scales - The distortions that appear in real business decks, and how to correct each.
- Colour, Contrast & Accessible Visualisation - Categorical and sequential palettes, contrast minimums, and colour-blind-safe choices.
- Tables, Small Multiples & When Text Beats a Chart - The cases where a well-built table or a single sentence outperforms any chart.
- Annotation: Making the Insight Impossible to Miss - Titles that state the finding, reference lines, and calling out the one thing that matters.
- Dashboard Design Principles: Layout, Hierarchy & Defaults - Reading order, grouping, sensible default filters, and what to delete before shipping.
- Designing for the Audience: Executive, Manager & Analyst Views - The same metric set laid out three ways for three very different readers.
- Chart Makeovers: Before and After, With the Reasoning - Real charts rebuilt step by step, with the reason for every change stated.
- Structuring an Insight Narrative for Decision-Makers - Situation, complication, finding, recommendation - and cutting everything else.
- Writing the Executive Summary Analysts Get Wrong - Leading with the answer, quantifying it, and stating what you want decided.
- Presenting Analysis and Handling Pushback - Defending a number without becoming defensive, and conceding correctly when wrong.
- Communicating Uncertainty Without Losing the Audience - Ranges, caveats and confidence stated in business language rather than statistics.
- Case Study: Turning One Messy Dataset into a One-Page Story - From raw extract to a single page that drives a decision, with the drafts shown.