Database Fundamentals Which term refers to the degree to which data in a database are accurate, correct, and consistent over their life cycle?

Introduction / Context:
Data quality underpins trustworthy analytics and operations. A core concept is data integrity, which encompasses accuracy, consistency, and completeness from creation through storage, transmission, and retrieval.

Given Data / Assumptions:

• Relational databases with constraints, transactions, and auditing.
• Need to prevent corruption, inconsistency, and unauthorized changes.

Concept / Approach:
Distinguish integrity from related terms. Security protects against unauthorized access; validity often refers to rule-based correctness at entry; independence separates data from application logic or storage structures. Integrity is the umbrella for accurate, reliable data over time.

Step-by-Step Solution:
Use constraints (primary/foreign keys, unique, check) to enforce structure.Apply ACID transactions to maintain consistent state despite failures.Audit and backup to detect and recover from anomalies.

Verification / Alternative check:
Consistency checks, referential integrity validations, and reconciliation reports demonstrate integrity adherence. Violations indicate integrity issues even if access control is strong.

Why Other Options Are Wrong:
Security (Option A) controls access, not accuracy per se.Validity (Option B) is typically a subset (e.g., format/range checks) at entry time.Independence (Option C) is architectural separation, not data correctness.

Common Pitfalls:

• Assuming security guarantees integrity—insider errors can still corrupt data.
• Relying solely on application checks without database constraints.

Final Answer:
Data integrity.