If your AI models on Databricks feel less accurate in production than in testing, the model isn’t the problem. The data is temporally wrong. Relying on batch replication for SQL databases creates a structural freshness floor that you cannot bypass simply by running jobs more frequently. Batch polling scans full tables, struggles with missing updated_at […]
