data-dashboard-design

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Translation

Chinese

Dashboard Design

仪表盘设计

Framework

框架

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

铁律：一个仪表盘，一类受众，一个目标

试图同时服务CEO、营销团队和工程师的仪表盘，最终无法很好地服务任何一方。每类受众有不同的问题、不同的指标和不同的时间范围。

CEO：“我们在增长吗？” → 北极星指标 + 收入 + 核心趋势
营销团队：“哪些营销活动有效？” → CAC、ROAS、渠道转化情况
工程师：“系统是否健康？” → 延迟、错误率、上线时间

KPI Hierarchy (Pyramid Structure)

KPI层级（金字塔结构）

          [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)

          [北极星指标]
         /                    \
    [L1：3-5个业务KPI]
       /         |         \
  [L2：每个KPI对应的驱动指标]
     /     |     |     |     \
[L3：诊断/运营指标]

北极星指标：最能体现价值交付的单一指标（日活跃用户DAU、月度经常性收入MRR、商品交易总额GMV）
L1：驱动北极星指标的业务KPI（留存率、获客量、变现能力）
L2：团队可以采取行动的驱动指标（转化率、每用户平均收入ARPU、流失率）
L3：用于问题排查的诊断指标（页面加载时间、错误率、漏斗步骤转化率）

Chart Type Selection

图表类型选择

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

问题	图表	原因
趋势如何？	折线图	展示随时间的变化
各分类如何对比？	柱状图（分类较多时用横向）	便于对比
构成情况如何？	堆叠柱状图或饼图（谨慎使用，不超过5个分片）	展示整体与部分的关系
分布情况如何？	直方图或箱线图	展示数据分布和异常值
变量间关系如何？	散点图	展示相关性
地理分布模式是什么？	地图/分级统计图	展示空间模式
单一数值展示？	计分卡/大数字	一目了然的状态呈现
与目标的差距如何？	仪表盘图或子弹图	跟踪进度

Design Principles

设计原则

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

5秒原则：仪表盘的核心信息应在5秒内清晰呈现
首屏可见：最重要的指标无需滚动即可查看
时间范围一致：默认情况下，一个仪表盘上的所有图表应使用相同的时间周期
色彩有意义：用色彩传递信息（红色=不良，绿色=良好），而非装饰
对比上下文：每个数值都需要上下文——与上期对比、与目标对比、与基准对比
渐进式披露：顶部展示摘要 → 点击/下钻查看详情

Dashboard Layers

仪表盘层级

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

层级	受众	刷新频率	内容
高管层	高管团队、董事会	每周/每月	5-8个KPI、趋势、告警
运营层	团队负责人	每日	10-15个指标，支持按团队/产品筛选
诊断层	分析师、工程师	实时至每小时	20+个指标、下钻功能、原始数据访问权限

Tool Comparison

工具对比

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

工具	最佳适用场景	成本	学习曲线
Tableau	复杂分析、大型数据集	$$$	中-高
Power BI	Microsoft生态、企业级	$$	中等
Looker	以SQL为核心的团队、数据建模	$$$	高
Metabase	快速部署、开源、自助服务	免费/付费	低
Google Sheets/Data Studio	简单场景、协作式、免费	免费	低
Grafana	基础设施/实时监控	免费/付费	中等

Output Format

输出格式

markdown

undefined

markdown

undefined

Dashboard Specification: {Name}

仪表盘规格：{Name}

Purpose & Audience

目标与受众

Audience: {who}
Key question: {what they need to answer}
Refresh: {real-time / daily / weekly}

受众：{who}
核心问题：{他们需要解答的问题}
刷新频率：{实时 / 每日 / 每周}

KPI Hierarchy

KPI层级

North Star: {metric}
L1 KPIs: {3-5 metrics}
L2 Driving Metrics: {per L1}

北极星指标：{metric}
L1 KPI：{3-5个指标}
L2 驱动指标：{对应每个L1的指标}

Layout

布局

Position	Component	Chart Type	Metric
Top-left	{scorecard}	Big number	{North Star}
Top-right	{trend}	Line chart	{key KPI over time}
Mid-left	{comparison}	Bar chart	{breakdown by segment}
...	...	...	...

位置	组件	图表类型	指标
左上角	{计分卡}	大数字	{北极星指标}
右上角	{趋势图}	折线图	{核心KPI随时间变化}
中左部	{对比图}	柱状图	{按细分维度拆解}
...	...	...	...

Filters

筛选器

Date range, product, segment, region

日期范围、产品、细分维度、地区

Alerts

告警

Metric	Threshold	Alert To
{metric}	{value}	{team/person}

undefined

指标	阈值	告警对象
{metric}	{数值}	{团队/个人}

undefined

Gotchas

注意事项

Dashboard ≠ report: A report explains what happened (narrative). A dashboard monitors what IS happening (real-time status). Don't make a dashboard that requires reading.
Pie charts are almost always wrong: Humans are bad at comparing angles. Use bar charts for composition with > 3 categories. Pie charts work only for 2-3 slices with very different sizes.
Too many metrics = no metrics: If everything is highlighted, nothing is. Limit executive dashboards to 5-8 metrics. More → use filters or drill-down.
Vanity metrics sneak in: Total users, page views, and downloads feel impressive but rarely drive action. Every metric on the dashboard should answer: "What would we do differently if this number changed?"
ETL reliability: A dashboard is only as good as its data pipeline. If data is stale, incomplete, or wrong, the dashboard becomes a liability. Show "last updated" timestamp prominently.

仪表盘≠报告：报告解释已发生的情况（叙事性）。仪表盘监控当前正在发生的情况（实时状态）。不要制作需要阅读的仪表盘。
饼图几乎总是不合适：人类不擅长比较角度。当分类超过3个时，用柱状图展示构成。饼图仅适用于2-3个分片且大小差异明显的情况。
指标过多等于没有重点：如果所有内容都被突出显示，就等于没有重点。高管仪表盘限制在5-8个指标。更多指标请使用筛选器或下钻功能。
虚荣指标容易混入：总用户数、页面浏览量、下载量看起来亮眼，但很少能指导行动。仪表盘上的每个指标都应该能回答：“如果这个数值变化，我们会采取什么不同的行动？”
ETL可靠性：仪表盘的质量取决于其数据管道。如果数据过时、不完整或错误，仪表盘会成为负担。请显眼地展示“最后更新时间”戳记。

References

参考资料

For dashboard wireframe templates, see
```
references/dashboard-templates.md
```
For SQL-based metric definitions, see
```
references/metric-definitions.md
```

如需仪表盘线框模板，请查看
```
references/dashboard-templates.md
```
如需基于SQL的指标定义，请查看
```
references/metric-definitions.md
```