A recent analysis of ENA trading on Ethereum revealed that only 37% of the reported 7-day volume was verified as genuine, with 94% of that volume concentrated within a two-day period driven by a single entity. This highlights the limitations of relying on simple volume metrics, as they can be heavily skewed by atypical activity and fail to accurately reflect true tradable depth. For those in the AI/ML/Data Science space, this underscores the importance of rigorous data validation and the need to look beyond surface-level metrics when assessing on-chain activity and token health.
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