data-storytelling – skill Dữ liệu & Khoa học cho agent AI

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