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Clinical 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

More case studies

Starbucks · 20 days → hours20 days of report assembly, down to hours — across 17 countriesRethinkFirst · 10x50+ hours a month saved, and new analysts productive in under two weeksMUFG · 19KYC standardised across 19 countries, and a week of Excel became 20 minutes

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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