data-storytelling

# 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