Data Storytelling
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Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.
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Frontmatter — 2 properties
| 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. |
| 1 | --- |
| 2 | name: data-storytelling |
| 3 | 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. |
| 4 | ---A5 — No allowed-tools declared — no way to tell what this skill may touch |
| 5 | |
| 6 | # Data Storytelling |
| 7 | |
| 8 | Transform raw data into compelling narratives that drive decisions and inspire action. |
| 9 | |
| 10 | ## When to Use This Skill |
| 11 | |
| 12 | - Presenting analytics to executives |
| 13 | - Creating quarterly business reviews |
| 14 | - Building investor presentations |
| 15 | - Writing data-driven reports |
| 16 | - Communicating insights to non-technical audiences |
| 17 | - Making recommendations based on data |
| 18 | |
| 19 | ## Core Concepts |
| 20 | |
| 21 | ### 1. Story Structure |
| 22 | |
| 23 | ``` |
| 24 | Setup → Conflict → Resolution |
| 25 | |
| 26 | Setup: Context and baseline |
| 27 | Conflict: The problem or opportunity |
| 28 | Resolution: Insights and recommendations |
| 29 | ``` |
| 30 | |
| 31 | ### 2. Narrative Arc |
| 32 | |
| 33 | ``` |
| 34 | 1. Hook: Grab attention with surprising insight |
| 35 | 2. Context: Establish the baseline |
| 36 | 3. Rising Action: Build through data points |
| 37 | 4. Climax: The key insight |
| 38 | 5. Resolution: Recommendations |
| 39 | 6. Call to Action: Next steps |
| 40 | ``` |
| 41 | |
| 42 | ### 3. Three Pillars |
| 43 | |
| 44 | | Pillar | Purpose | Components | |
| 45 | | ------------- | -------- | -------------------------------- | |
| 46 | | **Data** | Evidence | Numbers, trends, comparisons | |
| 47 | | **Narrative** | Meaning | Context, causation, implications | |
| 48 | | **Visuals** | Clarity | Charts, diagrams, highlights | |
| 49 | |
| 50 | ## Detailed patterns and worked examples |
| 51 | |
| 52 | Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient. |
| 53 | |
| 54 | ## Best Practices |
| 55 | |
| 56 | ### Do's |
| 57 | |
| 58 | - **Start with the "so what"** - Lead with insight |
| 59 | - **Use the rule of three** - Three points, three comparisons |
| 60 | - **Show, don't tell** - Let data speak |
| 61 | - **Make it personal** - Connect to audience goals |
| 62 | - **End with action** - Clear next steps |
| 63 | |
| 64 | ### Don'ts |
| 65 | |
| 66 | - **Don't data dump** - Curate ruthlessly |
| 67 | - **Don't bury the insight** - Front-load key findings |
| 68 | - **Don't use jargon** - Match audience vocabulary |
| 69 | - **Don't show methodology first** - Context, then method |
| 70 | - **Don't forget the narrative** - Numbers need meaning |
| 71 |
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