Impact of Small Data Errors

Small data errors can significantly impact AI models, leading to potential financial losses for enterprises. For instance, one example highlighted involved a major bank using outdated credit scores, which resulted in costly miscalculations in loan approvals. This emphasizes the critical need for accurate and up-to-date data to ensure AI models function effectively. By implementing data observability platforms, organizations can proactively identify and correct these errors before they escalate into larger issues.