What is a major consequence of denormalization?

Denormalization is a database design technique that involves combining tables or adding redundant data to optimize for read performance at the cost of write performance and data integrity. A major consequence of denormalization is data redundancy, which refers to the unnecessary duplication of data within a database. This can happen when data that would normally be split across multiple tables in a normalized database is instead stored in a single table.

While denormalization can improve performance for read operations by reducing the number of joins needed to retrieve data, it inherently introduces redundancy by storing the same piece of information in multiple places. This redundancy increases the risk of data inconsistency because updates must be made in multiple locations whenever the data changes. Therefore, option D accurately captures one of the central outcomes of denormalization, as it highlights the presence of extra copies of data within a database schema.