Data Verification vs. Data Validation

Data Verification vs. Data Validation

Data verification and data validation are both crucial processes in ensuring data quality, but they serve distinct purposes:

Data Verification is the process of confirming that the data provided is accurate, complete, and consistent. It aims to ensure that the data matches the source or input and is free from errors or discrepancies. Data verification can involve comparing the provided data against a trusted source or reference data to confirm its accuracy, cross-referencing data with official records, and conducting double-entry checks.

Data Validation ensures that the data meets certain standards, rules, or requirements. This involves applying various checks, such as format validation (e.g., ensuring dates are in the correct format), range validation (e.g., checking that numerical values fall within acceptable ranges), logical validation, etc.  

To sum it up data verification focuses on confirming the accuracy and consistency of data while data validation focuses on ensuring that the data meets specific standards or requirements.

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