Data verification is a process in which different types of data are checked for accuracy andinconsistencies afterdata migration is done.[1] In some domains it is referred to Source Data Verification (SDV), such as inclinical trials.[2]
Data verification helps to determine whether data was accurately translated when data istransferred from one source to another, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneousdata loss.
Methods for data verification includedouble data entry,proofreading and automated verification of data. Proofreading data involves someone checking the data entered against the original document. This is also time-consuming and costly. Automated verification of data can be achieved using one way hashes locally or through use of a SaaS based service such as Q by SoLVBL to provide immutable seals to allow verification of the original data.
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