How can you normalize data for consistent system development?

2 How to apply data normalization?

Data normalization is usually applied in stages, from the first normal form (1NF) to the fifth normal form (5NF), each with a specific criterion to meet. The higher the normal form, the more normalized the data is; however, this also causes the database to become more complex and fragmented. The most common normal forms include 1NF, which requires each table to have a primary key and each attribute to be atomic; 2NF, which requires that each table is in 1NF and each non-key attribute is fully dependent on the primary key; 3NF, which requires that each table is in 2NF and each non-key attribute is non-transitively dependent on the primary key; and BCNF, which requires that each table is in 3NF and each determinant is a candidate key.

5 When to use data denormalization?

Data denormalization is a technique that reverses or modifies aspects of data normalization, by adding redundant or derived data to a database, to optimize the trade-off between data quality and performance. This technique is often employed when the data is read-intensive, stable, and complex. Data denormalization can take various forms, such as adding derived attributes, redundant attributes, or combining/splitting tables. However, this should be done with caution and planning, as it can introduce data anomalies, compromise data integrity, and increase data maintenance. Therefore, data denormalization should be based on a careful analysis of system requirements, data characteristics, and user expectations - balanced with data normalization - to achieve the optimal level of quality and performance.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?