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Data from 100+ countries harmonised, processing time down 80%

Harmonising panel and retail data from more than 100 countries was a manual workflow that could not scale with client volume. Automated pipelines now do it with validation built in.

80%
faster processing
95%
accuracy on every output
90%
less manual effort

The workflow

What replaced the manual work

  • Panel data, 100+ countries
  • Retail data, 100+ countries
One pipeline
  • Connect
  • Clean
  • Automate
  • Share

Recorded once, re-run on a schedule.

  • Harmonised, standardised formats
  • Validation on every delivery

Outcomes

What changed

  • 80% reduction in processing time, so more volume without added headcount
  • 95% accuracy regardless of source country or data provider
  • 90% reduction in manual effort, freeing the data operations team for analysis
  • Standardised formats and automated validation on every delivery

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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