The biggest hidden risk is creating data silos and losing context. When every sensor makes its own optimized decisions, you can lose the raw, synchronized data stream needed to train new machine learning models or diagnose systemic issues. While optimizing for efficiency, you may sacrifice future analytical flexibility.
The biggest hidden risk is creating data silos and losing context. When every sensor makes its own optimized decisions, you can lose the raw, synchronized data stream needed to train new machine learning models or diagnose systemic issues. While optimizing for efficiency, you may sacrifice future analytical flexibility.
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The biggest hidden risk is creating data silos and losing context. When every sensor makes its own optimized decisions, you can lose the raw, synchronized data stream needed to train new machine learning models or diagnose systemic issues. While optimizing for efficiency, you may sacrifice future analytical flexibility.
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