What does denormalization entail in database management?

Denormalization in database management typically involves the process of combining tables to improve read performance. This practice is often employed in database design where normalized structures can lead to complex queries that necessitate numerous joins, which may slow down performance, particularly in systems where read operations are frequent.

By combining tables, denormalization aims to reduce the number of table joins required during query execution. This can lead to faster retrieval times as the database engine has fewer operations to perform to gather the needed data. Even though denormalization can introduce some level of data redundancy, the trade-off is often justified in scenarios where query performance is critical, such as in reporting and analytics platforms where speed is paramount.

The other options describe processes that do not align with the concept of denormalization: breaking tables into smaller pieces relates to normalization, creating additional indexes is an optimization technique but does not involve table structure changes as seen in denormalization, and changing data types for better compatibility is more about data integrity rather than the structural arrangement of tables in a denormalized setup.