/data-storytelling

name: data-storytelling
description: Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

Data Storytelling

Transform raw data into compelling narratives that drive decisions and inspire action.

When to Use This Skill

• Presenting analytics to executives
• Creating quarterly business reviews
• Building investor presentations
• Writing data-driven reports
• Communicating insights to non-technical audiences
• Making recommendations based on data

Core Concepts

1. Story Structure

Setup → Conflict → Resolution

Setup: Context and baseline
Conflict: The problem or opportunity
Resolution: Insights and recommendations

2. Narrative Arc

1. Hook: Grab attention with surprising insight
2. Context: Establish the baseline
3. Rising Action: Build through data points
4. Climax: The key insight
5. Resolution: Recommendations
6. Call to Action: Next steps

3. Three Pillars

| Pillar | Purpose | Components | | ------------- | -------- | -------------------------------- | | **Data** | Evidence | Numbers, trends, comparisons | | **Narrative** | Meaning | Context, causation, implications | | **Visuals** | Clarity | Charts, diagrams, highlights |

Detailed patterns and worked examples

Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient.

Best Practices

Do's

• **Start with the "so what"** - Lead with insight
• **Use the rule of three** - Three points, three comparisons
• **Show, don't tell** - Let data speak
• **Make it personal** - Connect to audience goals
• **End with action** - Clear next steps

Don'ts

• **Don't data dump** - Curate ruthlessly
• **Don't bury the insight** - Front-load key findings
• **Don't use jargon** - Match audience vocabulary
• **Don't show methodology first** - Context, then method
• **Don't forget the narrative** - Numbers need meaning