Measuring the importance of data quality to causal AI success
Dynatrace
JANUARY 4, 2024
Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. That’s where causal AI can help. Timeliness.
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