A field guide to dashboards
Learn the trade, then break ground.
What kinds of dashboards exist, which tool to reach for, how this site parses its own data — and the best free places to learn. Opinionated on purpose; every link is a primary source.
Six kinds of dashboard
Most dashboard failures are type errors — a real-time layout answering a strategic question. Decide the type first, then the tool.
📌 KPI / executive
A handful of headline numbers with trend and target — revenue, share, NPS. Read in ten seconds, updated on a schedule.
⚡ Operational / real-time
Live state of a system or campaign: traffic, conversions, error rates. Optimised for monitoring and alerting, not analysis.
🔬 Analytical / exploratory
Many linked filters and cross-sections so an analyst can slice the data themselves and hunt for the "why" behind a number.
🧭 Strategic
Long horizons and few updates: market sizing, country scoring, scenario comparison. Depth over freshness.
📖 Data story / scrollytelling
A fixed narrative with charts in a deliberate order. The author controls the path; the reader scrolls, not filters.
🗺️ Geospatial
The map is the interface: choropleths, point clusters, flows. Works when location itself carries the signal.
BI tools, honestly compared
There is no best tool, only a best fit. Rough rule: Metabase to give a team self-serve answers, Superset or Grafana to self-host seriously, Tableau or Power BI when the company already pays for them, Dash/Streamlit when the logic lives in Python, and D3 when the output must be exactly what you designed.
| Tool | Licence | Strongest at | Keep in mind |
|---|---|---|---|
| Tableau ↗ | Commercial | Deep visual exploration; the analyst drag-and-drop standard. Free publishing via Tableau Public. 👀 See it live: the World Happiness Report’s own viz ↗ | Desktop app; steep licence, gentle learning curve |
| Power BI ↗ | Commercial | Corporate reporting in Microsoft shops; tight Excel/Azure integration, DAX for modelling. 👀 See it live: Microsoft’s interactive sample report ↗ | Cheap per seat; Windows-centric |
| Apache Superset ↗ | Open source | Self-hosted BI over SQL databases; dashboards, SQL Lab, row-level security. The main OSS Tableau alternative. 👀 See it live: dashboard walkthrough with the real UI ↗ | Needs a server and some ops |
| Grafana ↗ | Open source | Time series and monitoring: metrics, logs, alerting. Less suited to ad-hoc table analytics. 👀 See it live: live time-series dashboard on Grafana Play ↗ | Try live demos at play.grafana.org |
| Metabase ↗ | Open source | The fastest "questions over a database" tool for non-analysts; five-minute setup. 👀 See it live: a live survey dashboard ↗ | Simpler charts than Superset |
| Looker Studio ↗ | Free (Google) | Free shareable dashboards over Google Analytics, Sheets and BigQuery. 👀 See it live: the report gallery — every report opens live ↗ | Weak outside the Google ecosystem |
| Plotly / Dash ↗ | Open source | Analytical web apps in pure Python — full control over interactivity and layout. 👀 See it live: the Dash app gallery, apps run live ↗ | You write code, not drag charts |
| Streamlit ↗ | Open source | Turning a Python script into an interactive app in an afternoon; ideal for prototypes and ML demos. 👀 See it live: the app gallery, apps run live ↗ | Reruns whole script per interaction |
| Observable ↗ | Freemium | JavaScript notebooks for bespoke D3 visuals; home of Observable Plot. 👀 See it live: a World Happiness Report notebook ↗ | For people who like code |
| Datawrapper ↗ | Freemium | Newsroom-grade single charts and maps with zero code; excellent defaults. 👀 See it live: Weekly Charts — live charts by their team ↗ | Charts, not full dashboards |
| Flourish ↗ | Freemium | Animated templates — bar chart races, scrollytelling — publishable in minutes. 👀 See it live: the template gallery, all interactive ↗ | Template-bound |
| D3 / hand-written SVG ↗ | Open source | Total control, zero dependencies, any design. Everything on BullDozer is built this way. 👀 See it live: our happiness story — this site is the demo ↗ | Slowest to build, most durable |
How BullDozer is built
This whole site is one worked example of a parsing-to-publication pipeline — no database, no BI licence, no server.
1 · Parse
Every dataset starts as a public file — IMF and World Bank APIs, survey CSVs from WVS, Afrobarometer or V-Dem, Excel sheets from research institutes. A parser script per source downloads it and reads it as-is.
2 · Normalise
Everything is reshaped into one long format: country · period · value, with ISO-3 codes and
a metadata block (source, licence, method, link). 136 datasets, one schema.
3 · Publish
A static site generator (Astro) bakes the JSON into pages and hand-written SVG charts at build time. The result is plain HTML on a CDN — fast, free to host, nothing to hack.
Practical parsing notes: prefer an official API or bulk-download over scraping HTML; keep the raw file and parse a copy; re-run on a schedule (GitHub Actions cron) rather than by hand; and record the source URL and access date next to the data — that is what makes “every number sourced” possible. Browse the results on Polls and Macro, or check definitions in the Glossary.
Free places to learn
A short list that is actually short — each entry earns its place.