BiotechClinical analysis time halved, 30+ research hours freed a month
Researchers were formatting clinical data by hand before they could analyse it, with error-prone manual steps in the middle. Validated pipelines now run those steps, and scientists edit them themselves.
- 50%
- faster analysis
- 30+
- research hours freed a month
- 75%
- better data reliability
The workflow
What replaced the manual work
- Clinical study data
One pipeline
- Connect
- Clean
- Automate
- Share
Recorded once, re-run on a schedule.
- Validated, consistent outputs
- Pipelines scientists edit themselves
Outcomes
What changed
- Over 30 hours of manual data handling freed every month
- Validated, consistent outputs replaced error-prone manual steps
- 75% improvement in data reliability, so results can be trusted and acted on
- 68% of pipeline edits made directly by scientists, with no IT ticket
What they used
The parts of Mammoth involved
- Data Engine
- Automated validation
- Scheduled refresh
- Custom roles
Start with one source and one question.
That's how this deployment began too. Twenty minutes on the free plan is a fair test.
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