How do you normalize or denormalize your database when business requirements or data sources change?

Database normalization is essentially the Marie Kondo method for your database: organizing and optimizing data to reduce redundancy and improve data integrity. Imagine breaking down a cluttered, overstuffed wardrobe into neatly organized drawers. Each "drawer" (table) holds specific and unique pieces (data) that relate logically, making everything easy to find and less messy.

La desnormalización reduce el número de tablas por lo tanto el número de uniones disminuye, así como la complejidad del modelo, lo cual lo hace más accesible. En ocasiones, un modelo normalizado requiere de una correcta gestión de las union, de las claves primarias, foráneas etc… En consultas complejas, esto puede ser un impedimento y si a?adimos una mala arquitectura de nuestra BBDD, la normalización puede convertirse en un “ enemigo”. Como todo, con un buen análisis de nuestra situación, sabremos elegir si lo mejor para nosotros es desnormalizar o normalizar

Conversely, denormalization is like deciding to keep some winter coats with your summer shorts because you switch between them frequently. It involves adding some redundancy back into your database to speed up complex queries, at the cost of increased storage and potential maintenance headaches. It’s a trade-off between storage space and speed, useful when your database needs to perform complex queries at lightning speed.

When your business needs or where your data comes from change, you might need to adjust your database to keep things organized. Normalizing means breaking down your data into smaller parts to avoid repeating info. You do this when you need to keep your database tidy and efficient.

Normalize when your data is as tangled as a bowl of spaghetti and you need to make sense of it all. This typically happens when data integrity and avoiding duplication are top priorities, such as when handling transactions or maintaining precise records in a CRM system. Normalization ensures that each piece of data lives in only one place, reducing the confusion and errors that can come from data redundancy.

Denormalize when performance becomes critical and your queries need to run faster than Usain Bolt. This is particularly useful in read-heavy databases where speed trumps the cost of additional storage and a little data redundancy doesn’t cause too much heartache. It’s like keeping your tools on the counter during a marathon cooking session, sacrificing cleanliness for speed.

Normalizing your database involves creating tables that store related data and defining relationships between them using keys. Start by identifying entities and their relationships, proceed to eliminate redundancy by ensuring that each piece of information is stored only once, and use foreign keys to link data tables efficiently.

Denormalization, on the other hand, might involve merging tables or adding redundant data to existing tables. This could mean adding frequently accessed but rarely updated data directly into a table where it’s often needed, to avoid complex joins that could slow down query performance.

When faced with changing business requirements or data sources, the approach to normalization or denormalization depends on the specific scenario. If the changes result in complex or evolving data relationships, normalization may be necessary to maintain data integrity and reduce redundancy. This involves organizing data into separate tables based on functional dependencies and eliminating data anomalies. On the other hand, if performance becomes a priority or data access patterns shift, denormalization may be beneficial. This involves combining tables or duplicating data to optimize query performance and simplify data retrieval.

When adjusting your database structure, always keep a keen eye on the future. How will changes impact scalability, maintenance, and overall performance? What are the security implications? Consider the trade-offs between complexity and performance carefully. And remember, like any good strategy game, the moves you make now can set the stage for either triumph or trouble down the line. Think it through, plan meticulously, and always be ready to iterate based on new information and changing business needs.