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data operations
Simple ETL flow that feels useful from day one.
Prototype
A light workflow canvas for moving source data through a clean, validate, and publish pipeline without the complexity of a full data platform.
Pipeline
Live demoSource data
Raw import feed
| Customer | Region | Revenue | Status |
|---|---|---|---|
| Ava Lim | North | USD 1200 | paid |
| Marcus Chen | West | USD 2400 | pending |
| Nina Patel | South | USD 980 | paid |
| Rafael Gomez | — | USD - | failed |
| Sophia Turner | East | EUR 4300 | paid |
| Daniel Moore | Central | USD 3100 | paid |
Transformed output
Warehouse preview
| Customer | Region | Revenue | Status |
|---|---|---|---|
| Ava Lim | North | USD 1,200 | Paid |
| Marcus Chen | West | USD 2,400 | Pending |
| Nina Patel | South | USD 980 | Paid |
| Rafael Gomez | Unassigned | USD 0 | Review |
what this helps with
A useful ETL flow, not a noisy dashboard.
Pull source data
Connect raw feeds from spreadsheets, exports, or internal apps without overengineering the first step.
Clean and standardize
Normalize records so the data is ready for downstream reporting, reuse, and analysis.
Publish to reporting
Send the final table to dashboards and teams that need a reliable, simple, trustable dataset.
Best fit
Useful workflow prototypes for small operations teams.
Production-minded