What is the main purpose of denormalization?

The primary purpose of denormalization is to enhance performance by duplicating information. In a normalized database design, data is structured to reduce redundancy, which can create multiple related tables. While this structure is beneficial for data integrity and consistency, querying such a design can become complex and inefficient, particularly when multiple joins are required to retrieve needed data.

Denormalization addresses performance issues by intentionally introducing redundancy. By adding copies of data or combining tables, the system can reduce the number of joins required in queries, subsequently speeding up data retrieval times. This approach is especially useful in environments where read operations significantly outperform write operations, such as data warehousing and reporting applications.

In contrast, the other options play supportive roles in database management but don't directly align with the main objective of denormalization. Facilitating data reporting is a potential benefit of denormalization but is more of a secondary outcome rather than the primary aim. Ensuring data consistency across databases typically pertains to normalization, where data integrity is prioritized. Finally, simplifying the database schema can be a side effect of denormalization but is not the core purpose; rather, denormalization can often lead to a more complex schema due to the addition of redundant data.