Data integrity refers to the accuracy, consistency, and reliability of data in an information system, especially in a database. It ensures that data is correct and dependable, meeting the expected standards. Data integrity encompasses various aspects:
Uniqueness: Data integrity ensures that records in a database are unique and free from duplicates, often achieved through the use of primary keys, which guarantee each record has a unique identifier.
Completeness: Complete data integrity ensures that all necessary data is present in a database, with no missing values or empty fields.
Accuracy: Data must be correct and precise, reflecting real-world conditions or actual facts accurately.
Consistency: Data integrity ensures that data is consistent and does not contain conflicting information. Data related across different parts of the system or in different tables should be in harmony.
Integrity Rules: Databases can use integrity rules to enforce that entered data meets required criteria. For example, integrity rules can mandate that a specific date field contains a valid date.
Security: Data integrity also involves protection against unauthorized alterations or deletions of data. Security measures, such as permissions and access controls, are implemented to safeguard data from unauthorized access.
Maintaining data integrity is crucial for the reliable operation of information systems and databases as it ensures that the stored data is trustworthy and meaningful. Data integrity is a central concept in database management and data management in general.
DynamoDB
