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Data perturbation is a privacy-preserving technique used in data mining to modify the data in such a way that the individual values are obscured while maintaining overall dataset utility for analysis. It is especially important in fields where data sensitivity and privacy are a concern, enabling insights to be drawn from data without compromising individual privacy.
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