Ship the dashboard, skip the BI tool
Plotly, Chart.js, Vega, pandas .to_html(): the modern data stack is great at exporting a self-contained HTML dashboard. Then it sits on your laptop, and the question becomes how to share a 'dashboard.html' without standing up a BI platform.
Drop it on htmldrop. Your team gets a stable URL to bookmark, and your cron job can re-publish fresh numbers to the same slug every morning.
Works with any charting export
If your tool can produce a single HTML file with inlined JS, it renders on htmldrop exactly as it does locally.
Refresh on a schedule
A few lines of Python in a cron job can PUT updated HTML to the same slug, turning a static export into a living dashboard.
Gate sensitive numbers
Revenue dashboards can sit behind a Pro password while public metrics stay open.
Common questions
- My Plotly export is bigger than 2 MB. What now?
- Load plotly.js from its CDN instead of inlining it (include_plotlyjs='cdn' in Python) and exports usually drop well under the limit.
- Can the dashboard fetch live data?
- Yes, client-side fetch to any API that allows cross-origin requests works inside the page.
- Do view counts work for dashboards?
- Every artifact tracks total views, which is a handy proxy for whether the team actually checks the numbers.