denormalisoituun

Denormalisoituun is a Finnish term that translates to "denormalized" in English, commonly used in the context of database design. In relational database theory, normalization is a process of organizing data to reduce redundancy and improve data integrity. This is achieved by dividing larger tables into smaller, more manageable tables and defining relationships between them. Denormalization, conversely, is the process of intentionally introducing some redundancy into a database by adding duplicate data or grouping data together.

The primary goal of denormalization is to improve read performance. By combining data that would otherwise require joins across multiple tables, queries can be executed more quickly. This is particularly beneficial in applications where read operations are much more frequent than write operations, such as in data warehousing and business intelligence systems. Denormalization can also simplify queries by reducing the need for complex joins.

However, denormalization comes with trade-offs. The introduction of redundancy can lead to increased storage requirements and potential data inconsistencies if not managed carefully. Updates, insertions, and deletions can become more complex and time-consuming as redundant data needs to be updated across multiple locations. Therefore, denormalization is typically applied strategically after a database has been normalized, and only when performance bottlenecks are identified that cannot be resolved through other means. It's a performance optimization technique, not a fundamental design principle like normalization.