What is a consequence of data redundancy in database design?

• A. Increased data security
• B. Potential inconsistencies
• C. Faster retrieval times
• D. Improved data relationships

Answer: (B)

Data redundancy in database design refers to the unnecessary duplication of data across the database. When the same data is stored in multiple locations, it heightens the risk of discrepancies. This means if one instance of the data is updated, but the other instances are not, it can lead to potential inconsistencies within the database.

For example, consider a scenario where customer information is stored in multiple tables. If a customer's address is updated in one table but not in another, the database may present varying information about that customer. Such inconsistencies can undermine data integrity and lead to errors in reporting or decision-making based on that data.

This emphasizes why reducing data redundancy is crucial in designing a database effectively. Making sure that each piece of information is stored in one place helps maintain accuracy and reliability across the system. The other options suggest outcomes that are generally not associated with redundancy. Increased security, faster retrieval times, and improved relationships are optimal outcomes of well-structured, normalized databases, rather than consequences of data redundancy.