Quick Study Revision Points: Data Integrity and Constraints

Quick Study Revision Points: Data Integrity and Constraints

Data Integrity:

  1. Definition: Data integrity refers to the accuracy, consistency, and reliability of data stored in a database over its entire lifecycle.

  2. Importance of Data Integrity:

    • Ensures the reliability and trustworthiness of data.

    • Guarantees that data meets certain standards and constraints.

    • Prevents data corruption, loss, or unauthorized modifications.

  3. Types of Data Integrity:

    • Entity Integrity: Ensures that each row in a table is uniquely identified by a primary key and that the primary key column does not contain null values.

    • Referential Integrity: Maintains the consistency between related tables by enforcing relationships and preventing orphaned or inconsistent data.

    • Domain Integrity: Ensures that data within a column adheres to specified data types, formats, ranges, or constraints.

    • User-defined Integrity: Additional integrity rules defined by users or application requirements.

  4. Techniques for Enforcing Data Integrity:

    • Primary Keys: Establishes a unique identifier for each row in a table.

    • Foreign Keys: Defines relationships between tables and ensures referential integrity.

    • Check Constraints: Defines specific conditions that data must meet to maintain integrity.

    • Data Validation: Verifies the accuracy and integrity of data before it is entered into the database.

    • Triggers: Automatically executes actions or validations based on specified events or conditions.

Constraints:

  1. Definition: Constraints are rules or conditions that are applied to the data in a database to enforce integrity, consistency, and validity.

  2. Common Types of Constraints:

    • Primary Key Constraint: Ensures that the primary key column(s) contain unique and non-null values.

    • Foreign Key Constraint: Enforces referential integrity by ensuring that values in a column match values in a related table's primary key.

    • Unique Constraint: Ensures that the values in a column or a combination of columns are unique.

    • Check Constraint: Validates that data meets specific conditions or expressions.

    • Not Null Constraint: Requires a column to contain a non-null value.

    • Default Constraint: Specifies a default value for a column when no value is provided during insertion.

  3. Purpose of Constraints:

    • Maintain data integrity and consistency.

    • Prevent invalid or inconsistent data from being inserted, updated, or deleted.

    • Enforce business rules and data validation requirements.

    • Improve data quality and reliability.

  4. Benefits of Constraints:

    • Promote data integrity and accuracy.

    • Improve data consistency and reliability.

    • Simplify application logic by offloading data validation to the database.

    • Enhance data protection and security.

    • Provide better error handling and error reporting.