Flag outliers, flatlines, and icing in Moli – all reviewed in the platform, before your data leaves.
In a real campaign, 2% of your records might have a data quality problem. Or 17%.
You only find out when you go looking, so we built QC into Moli to make that easier.
Moli QC brings that step into the platform. Rules run automatically on import and on all existing data, so problems are flagged from the moment your data arrives. For each flag type you get a dedicated review screen with time series charts, statistics, and a per-sensor breakdown.
How it works
We’re starting with three flag types:
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1
Outlier. Flags wind speed or direction values outside physically plausible ranges.
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2
Flatline. Flags sensors reporting the same value for an extended period.
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3
Icing (met mast only). Flags anemometers and wind vanes showing signs of icing, based on wind speed, standard deviation, and temperature thresholds.
Rules are configurable; set the thresholds that match your own QC methodology.
This is a beta release. We’re starting with a small group so we can work through feedback properly before rolling it out more broadly.
Join the Moli QC beta
We’re onboarding a small group of beta testers. Write to support@enerlace.de to get access.