Explain the term “referential integrity”. why is it important in a database?

Question: Explain the term “referential integrity”. why is it important in a database?

Referential integrity is a property of data that ensures that all its references are valid and consistent. In other words, it means that if one table (or relation) has a column (or attribute) that refers to another table's column, then the value of the referring column must exist in the referred column. This way, the data in the database is accurate and complete, and there are no orphaned or dangling records.

For example, suppose we have two tables: Customers and Orders. The Customers table has a primary key called CustomerID, which uniquely identifies each customer. The Orders table has a foreign key called CustomerID, which links each order to the customer who placed it. Referential integrity requires that every value of CustomerID in the Orders table must match a value of CustomerID in the Customers table. Otherwise, we would have orders that belong to no customer, or customers that have no orders.

Referential integrity is important in a database because it maintains the quality and reliability of the data. It prevents data anomalies, such as insertion, deletion, or update anomalies, that could compromise the meaning and consistency of the data. It also ensures that the database reflects the real-world entities and relationships that it models.

There are different ways to enforce referential integrity in a relational database management system (RDBMS). One way is to use constraints, such as foreign key constraints, that specify the rules for referential integrity and check them whenever data is modified. Another way is to use triggers, which are actions that are executed automatically when certain events occur, such as inserting, deleting, or updating data. Triggers can perform additional operations to maintain referential integrity, such as cascading updates or deletes.

Referential integrity is a subset of data integrity, which is a broader concept that covers the accuracy and consistency of all data in a database. Data integrity can be achieved by using various techniques, such as normalization, validation, encryption, backup, and recovery.

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