Keep ML training datasets updated with incoming signals
Keep ML training datasets updated with incoming signals
Data engineers miss incoming signal events, causing gaps in training data and blindspots in monitoring. It ingests signals into a central ML dataset so models evaluate using current records.
Overview
Missing signal records create blindspots that can undermine model quality and slow trading analysts. This workflow captures, validates, and tags every incoming signal into a central ML dataset, eliminating gaps so data engineers and analysts can evaluate and monitor models with reliable inputs.
Notable Features
- Check signal format on arrival
- Prevent duplicate signal records
- Add timestamp and source tags