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| definition | Data that contain errors. Can be caused by a number of factors including: inaccurate, incomplete or erroneous data such as spelling or punctuation errors, incorrect data or incorrect data type associated with a field, incomplete or outdated data, duplicate data, inconsistent data, incorrectly ordered data, improper parsing of fields from disparate systems, etc. Using a dirty dataset can lead to spurious associations, false conclusions and misdirected investments. | ||||||
| editorial note | Expert review decision, 2021-22: No review this cycle | ||||||
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| top concept of | rdmt original | ||||||