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. It removes much of the guesswork of untangling complex system issues and establishes with certainty why a problem occurred. Fragmented and siloed data storage can create inconsistencies and redundancies. Timeliness.
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