Dashboards anyone can build.
Stop being a ticket queue. Describe the analysis, connect the warehouse, and publish a cross-filtering dashboard — without waiting on a BI rollout.
Building it now — a hosted page, live, in seconds.
Q3 Revenue
| Region | Revenue | Δ |
|---|---|---|
| AMER | $612k | +18% |
| EMEA | $284k | −6% |
| APAC | $174k | +9% |
Analysts and data teams use ShareOut to turn warehouse queries into live, cross-filtering dashboards anyone can build — without a BI rollout, a licensing project, or a weeks-deep ticket backlog. You connect Snowflake, BigQuery, or any source once, describe the view, and publish a governed link everyone reads from. It is the speed of a spreadsheet with the trust of a real data connection, and it lets the rest of the team self-serve while you govern.
BI tools are heavy; spreadsheets are fragile.
Stakeholders want answers now, but the dashboard backlog is weeks deep and the "quick" spreadsheet breaks the moment someone edits it.
From query to dashboard
Point at the warehouse, describe the view, and get a real cross-filtering dashboard in minutes.
One source of truth
Everyone reads the same live numbers from the same connection — no more "which export is right?".
Reports that send themselves
Schedule a crew to query, summarize, and post the read-out to Slack every Monday.
How analysts use ShareOut
- 1
Connect the warehouse
Point ShareOut at Snowflake, BigQuery, Postgres, or a Sheet with your own credentials. One connection, read live — no extracts, no nightly export jobs to babysit.
- 2
Describe the analysis
Say what you want to see — "weekly revenue by region with a cohort filter" — and get a real cross-filtering dashboard. Refine it in the browser instead of hand-building charts.
- 3
Publish one source of truth
Share a governed link. Everyone reads the same live numbers from the same connection, so the "which export is right?" debate disappears.
- 4
Automate the read-out
Schedule a crew to query, summarize, and deliver the Monday report to Slack or email on its own — reporting that sends itself, freeing you from the recurring ask.
See it running.
What analysts build with ShareOut
"We cut our ad-hoc dashboard requests in half. People just build their own and we govern it."
Questions, answered
How do analysts build a dashboard with ShareOut?
Point at your warehouse or database, describe the view you want in plain language, and ShareOut publishes a real, cross-filtering dashboard in minutes. No BI rollout, no ticket queue — you go from query to a shareable live page without waiting weeks.
Does it connect to Snowflake, BigQuery, or my warehouse?
Yes. ShareOut connects to Snowflake, BigQuery, Postgres, Google Sheets, and any REST API using your own credentials. Dashboards read live from the source, so everyone sees the same current numbers from one connection.
How is this different from Tableau, Looker, or a spreadsheet?
Heavy BI tools mean rollouts, licenses, and a backlog; spreadsheets break the moment someone edits them. ShareOut sits in between: describe-to-build dashboards that connect to the warehouse, publish as a link, and stay governed — without the weight of a BI deployment or the fragility of a shared sheet.
Can reports run and send themselves?
Yes. Schedule a crew to query the warehouse, summarize the result, and post the read-out to Slack, email, or Telegram on a schedule — so the Monday metrics arrive on their own, no one re-running anything.
Can the whole team build without breaking governance?
That is the point. Stakeholders build their own views from governed connections in the team workspace, with roles and one source of truth — so you stop being a ticket queue while keeping the numbers trustworthy.