data-dashboard-design

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---
name: "data-dashboard-design"
description: "Design effective data dashboards with proper KPI hierarchy, chart type selection, and interactive features. Use this skill when the user needs to create a dashboard, choose the right visualizations, organize metrics for different audiences, or evaluate dashboard tools — even if they say 'build a dashboard', 'our reports are confusing', 'which chart should I use', or 'executives can't find the metrics they need'."
metadata:
  category: "WP-04 數據分析"
  tags: ["data-analysis", "dashboard", "visualization", "bi"]
---

# Dashboard Design

## Framework

```
IRON LAW: One Dashboard, One Audience, One Purpose

A dashboard that tries to serve the CEO, the marketing team, AND the
engineers will serve none of them well. Each audience has different
questions, different metrics, and different time horizons.

CEO: "Are we growing?" → North Star + revenue + key trends
Marketing: "Which campaigns work?" → CAC, ROAS, conversion by channel
Engineering: "Is the system healthy?" → Latency, error rate, uptime
```

### KPI Hierarchy (Pyramid Structure)

```
          [North Star Metric]
         /                    \
    [L1: 3-5 Business KPIs]
       /         |         \
  [L2: Driving Metrics per KPI]
     /     |     |     |     \
[L3: Diagnostic / Operational Metrics]
```

- **North Star**: ONE metric that best captures value delivery (DAU, MRR, GMV)
- **L1**: Business KPIs that drive the North Star (retention, acquisition, monetization)
- **L2**: Driving metrics teams can act on (conversion rate, ARPU, churn rate)
- **L3**: Diagnostic metrics for debugging (page load time, error rate, funnel step conversion)

### Chart Type Selection

| Question | Chart | Why |
|----------|-------|-----|
| How is the trend? | **Line chart** | Shows change over time |
| How do categories compare? | **Bar chart** (horizontal for many categories) | Easy comparison |
| What's the composition? | **Stacked bar** or **pie** (use sparingly, < 5 slices) | Shows parts of whole |
| What's the distribution? | **Histogram** or **box plot** | Shows spread and outliers |
| What's the relationship? | **Scatter plot** | Shows correlation |
| Where's the geographic pattern? | **Map / choropleth** | Spatial patterns |
| What's the single number? | **Scorecard / big number** | At-a-glance status |
| How are we vs target? | **Gauge** or **bullet chart** | Progress tracking |

### Design Principles

1. **5-second rule**: The dashboard's main message should be clear within 5 seconds
2. **Above the fold**: Most important metrics visible without scrolling
3. **Consistent time range**: All charts on one dashboard should use the same time period by default
4. **Color with purpose**: Use color to encode meaning (red = bad, green = good), not decoration
5. **Comparison context**: Every number needs context — vs prior period, vs target, vs benchmark
6. **Progressive disclosure**: Summary at top → click/drill to detail

### Dashboard Layers

| Layer | Audience | Refresh | Content |
|-------|---------|---------|---------|
| **Executive** | C-suite, board | Weekly/monthly | 5-8 KPIs, trends, alerts |
| **Operational** | Team leads | Daily | 10-15 metrics, filters by team/product |
| **Diagnostic** | Analysts, engineers | Real-time to hourly | 20+ metrics, drill-down, raw data access |

### Tool Comparison

| Tool | Best For | Cost | Learning Curve |
|------|---------|------|---------------|
| **Tableau** | Complex analysis, large datasets | $$$ | Medium-High |
| **Power BI** | Microsoft ecosystem, enterprise | $$ | Medium |
| **Looker** | SQL-centric teams, data modeling | $$$ | High |
| **Metabase** | Quick setup, open-source, self-serve | Free/$ | Low |
| **Google Sheets/Data Studio** | Simple, collaborative, free | Free | Low |
| **Grafana** | Infrastructure/real-time monitoring | Free/$ | Medium |

## Output Format

```markdown
# Dashboard Specification: {Name}

## Purpose & Audience
- Audience: {who}
- Key question: {what they need to answ