Abstract: This disclosure describes techniques for performing data remediation. In one example, this disclosure describes a method that includes identifying a plurality of stale files; applying a classification model to each of the plurality of stale files; identifying a plurality of unclassified files, wherein each of the unclassified files is one of the plurality of stale files that the classification model was not able to classify with a confidence level that exceeds a threshold confidence level; updating the classification model, over a period of time, to generate an evolved classification model; applying the evolved classification model to each of the unclassified files; identifying a subset of the unclassified files that the evolved classification model was not able to classify with a confidence level that exceeds the threshold confidence level; and deleting each of the files in the subset of the unclassified files.

Abstract: This disclosure describes techniques for performing data remediation. In one example, this disclosure describes a method that includes identifying a plurality of stale files; applying a classification model to each of the plurality of stale files; identifying a plurality of unclassified files, wherein each of the unclassified files is one of the plurality of stale files that the classification model was not able to classify with a confidence level that exceeds a threshold confidence level; updating the classification model, over a period of time, to generate an evolved classification model; applying the evolved classification model to each of the unclassified files; identifying a subset of the unclassified files that the evolved classification model was not able to classify with a confidence level that exceeds the threshold confidence level; and deleting each of the files in the subset of the unclassified files.

Abstract: This disclosure describes techniques for performing data remediation. In one example, this disclosure describes a method that includes identifying a plurality of stale files; applying a classification model to each of the plurality of stale files; identifying a plurality of unclassified files, wherein each of the unclassified files is one of the plurality of stale files that the classification model was not able to classify with a confidence level that exceeds a threshold confidence level; updating the classification model, over a period of time, to generate an evolved classification model; applying the evolved classification model to each of the unclassified files; identifying a subset of the unclassified files that the evolved classification model was not able to classify with a confidence level that exceeds the threshold confidence level; and deleting each of the files in the subset of the unclassified files.