Data validation
Data Validation
Data validation (pronunciation: /ˈdeɪtə ˌvælɪˈdeɪʃən/) is a process in the field of computing and data management that checks the accuracy and quality of data before it is input or processed. The term originates from the English words "data", meaning facts or statistics collected for reference or analysis, and "validation", meaning to check or prove the validity or accuracy of something.
Purpose
The main purpose of data validation is to ensure that the data collected is clean, correct, and useful. This is achieved by applying a set of validation rules or check routines that the data must comply with before it is considered valid. These rules can be as simple as checking if a field is filled in a form, or as complex as verifying the consistency of data across multiple databases.
Types of Data Validation
There are several types of data validation, including:
- Range check: This checks that the data falls within a certain range.
- Format check: This checks that the data is in the correct format.
- Existence check: This checks that the data actually exists.
- Uniqueness check: This checks that the data is unique and not duplicated.
- Consistency check: This checks that the data is consistent across all fields.
Related Terms
- Data cleansing: This is the process of detecting and correcting or removing corrupt or inaccurate records from a record set, table, or database.
- Data integrity: This is the maintenance and assurance of data accuracy and consistency over its entire life-cycle.
- Data verification: This is the process of checking that a product, system, or component meets specified requirements.
External links
- Medical encyclopedia article on Data validation
- Wikipedia's article - Data validation
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