About semi-normalization techniques
This is an article about semi-normalization techniques.
Hello!
Performance is a critical factor in database design.
Optimizing the performance of lookup operations is critical, especially in large databases or online Analytical Processing (OLAP) environments.
For this, a strategy called semi-normalization is used.
Today, weโre going to talk about semi-normalization.
What is semi-regularization?
Semi-normalization is a technique that improves the performance of lookup operations by re-combining normalized tables.
It is mainly used in OLAP environments with many read operations, the process of increasing data redundancy and putting some normalized tables back together.
the goal of semi-normalization
- Improves inquiry performance: Improves the performance of frequently occurring inquiry operations.
- Reduce response times: Reduce response times when running complex queries.
- Save storage: Add redundant data to save storage space and optimize database capacity.
Major semi-normalization techniques
- Pair tables: Reunite normalized tables to optimize lookup operations.
- Add redundant data: Adds redundant data to improve lookup performance.
- Add calculated fields: Perform operations of data in advance, save it, and use it during query.
Example
When dealing with customer order data, order information, customer information, and product information are stored separately in a normalized table.
By semi-normalizing this, you can improve the performance of lookup operations by storing customer and product information in duplicate in the order table.
at the end of the day
Semi-normalization is one of the critical strategies for improving the performance of databases.
The user experience can be enhanced by re-combining normalized tables and adding redundant data to optimize lookup performance.
However, care must be taken to maintain data consistency and accuracy when applying semi-normalization.
Thatโs it for the introduction of semi-regularization. See you again next time!