Data integrity is expressed in terms of

Explanation

● Data Integrity: Data integrity refers to the accuracy, completeness, and consistency of data over its entire lifecycle. It ensures that data is reliable and trustworthy for the purposes for which it is intended.● Constraints: Constraints are rules that define the valid values that can be stored in a database column. They help to enforce data integrity by preventing invalid or inconsistent data from being entered.● Consistency Rules: Consistency rules are broader than constraints and can encompass any rule that helps to ensure data integrity. This can include things like referential integrity, which ensures that relationships between tables are maintained, and business rules, which reflect the specific requirements of an organization.● Functional Dependency: A functional dependency exists when a single attribute (determinant) determines another attribute (dependent) in a table. This means that for every value of the determinant attribute, there is a unique corresponding value of the dependent attribute. Functional dependencies are relevant to data integrity because they can help to identify potential anomalies (errors or inconsistencies) in data.In conclusion:● Constraints, consistency rules, and functional dependencies all play a role in maintaining data integrity. Constraints enforce specific data validation rules. Consistency rules encompass a wider range of data quality checks. Functional dependencies help identify potential data anomalies. Because all three contribute to data integrity, the most accurate answer is that data integrity is expressed in terms of all of the above