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Data validation is the process of ensuring that the data collected, stored, or processed is accurate, consistent, and reliable. Various techniques can be used for data validation, depending on the type of data and the desired level of validation. Some common data validation techniques include:
Rule-based validation: Applying a predefined set of rules or criteria to check the data for accuracy, consistency, and proper formatting. Examples of rules include format rules, range rules, consistency rules, and lookup rules.
Constraint-based validation: Enforcing data constraints, such as unique keys, foreign keys, or check constraints, to ensure data integrity and consistency within a database.
Explore the full article for data validation techniques:
Rule-based validation: Applying a predefined set of rules or criteria to check the data for accuracy, consistency, and proper formatting. Examples of rules include format rules, range rules, consistency rules, and lookup rules.
Constraint-based validation: Enforcing data constraints, such as unique keys, foreign keys, or check constraints, to ensure data integrity and consistency within a database.
Explore the full article for data validation techniques:
