Data cleansing or data scrubbing to a dataset or table on the right
After cleaning, other similar system in the dataset as a dataset is compatible with all consistencies are removed. From the data validation process, and the removal of the type of error and to record. Data transformation, statistical methods, parsing (syntax error detection) and the known techniques such as the elimination of duplicate data are used for cleaning. Nice and clean data necessary to the criteria described below:
Accuracy: density, including the integrity and stability.
Completeness of missing data must be corrected.
Data the total number of density values omitted in the ratio of the rates generally known.
Consistency is concerned with the challenges and differences in meaning.
Uniformity is focused on irregularities or indiscretions.
Integrity: soundness and completeness criteria for a combined price.
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2012年9月18日星期二
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