Data Validation and Verification

Data validation is the process of checking whether data meets certain criteria prior to input or after data transfer.
Data validation can prevent errors at the time of data input, reducing the need for further corrections and increasing speed and efficiency of data processing.
Some common types of validation include range check, length check, and presence check.
A range check ensures data falls within a specific range. For example, for a date of birth field, the acceptable range might be any date from 100 years ago to the present day.
A length check verifies the data has a specific length. For example, in a UK-based telephone number field, it should accept only 11 digits.
A presence check ensures that a required field has not been left blank.
Other validation methods include format check (ensuring data follows a certain format, such as a post code), and lookup check (values are from a predefined list).

Data verification is the process of checking that data has been accurately entered or transferred.
Verification aims to confirm that the original data matches the data that was input or transferred.
Common methods of verification include double-entry and proofreading.
Double-entry verification requires the user to enter the same data twice. The second entry is then compared with the first to detect any discrepancies.
Proofreading, on the other hand, involves comparing the entered data to the original document or data source to spot any errors.

Both data validation and verification are key to ensuring the accuracy and consistency of data.
By minimising data errors, these processes improve the quality of data, making it more reliable and useful.
They save time and resources by reducing the need for later corrections, and avoid potential issues that could arise from incorrect or inconsistent data.

Data validation and Data verification are crucial processes in the handling of data.
They aim to ensure that data is accurate, consistent, and meets certain criteria, improving overall data quality.
Common methods of data validation include range, length, and presence checks, while data verification methods include double-entry and proofreading.