Understanding data drift is crucial for maintaining model performance. Amber highlights the importance of setting up monitors for every feature across model versions, ensuring teams receive timely alerts via Slack or email when performance issues arise. Additionally, unstructured data can be transformed into embeddings, allowing for a similar comparison against baseline distributions to detect anomalies.
