Q21: What is Denormalization and when should it be applied?
Denormalization intentionally introduces redundant data or pre-aggregated summary columns into a normalized schema.
While normalization optimizes data integrity and write performance, denormalization optimizes read latency in high-scale analytical databases (OLAP) or read-heavy applications by minimizing expensive JOIN operations.
Key Takeaways
- Denormalization improves read query speeds at the expense of storage space and potential write anomalies.
- Commonly used in data warehouses, star schema topologies, and read-heavy analytics systems.