Database Management: An Art, Not a Science – The Case Against Over-normalizing Data for Rapid Application Development | Blog


Database Management: An Art, Not a Science – The Case Against Over-normalizing Data for Rapid Application Development

Database Management

When it comes to data management, many often tout the virtues of rigorous normalization. It’s a practice that lends itself well to stringent and perfectly structured databases. That’s not to say however, that it’s the go-to strategy for every situation. Particularly in the context of rapid application development, a one-size-fits-all approach isn’t always the best solution.

Government institutions dealing with large troves of data need to prioritize efficiency and functionality. Sometimes, this means foregoing a fully normalized database in favor of one that allows for more rapid application development. We’ll delve into why this philosophy holds water and how the low-code versatility of supports it.

The Challenge of Over-normalization


Normalization is a widely practiced database technique intended to minimize redundancy and dependencies. In theory, it’s a great way to streamline data storage. However, if one’s end goal is rapid application development, a hyper-normalized database architecture can bring its fair share of challenges.

This primarily stems from the inverse relationship between the level of normalization and the level of data model complexity. By increasing your normalization level, you may wind up with an overly complex data model – hence reducing your development speed substantially. For real-world examples of this, look no further than the infamous challenges posed by 311 services management.

Striking the Right Balance


While we highlight the potential downside of over-normalization, it’s crucial to state that the goal is not to eliminate normalization but strike an artful balance. This is where heads the call through its patented operations management features.

Ignatius allows governments to control their data without the need for a fully normalized database, enabling them to work within a structure that supports rapid application development. Ignatius’s auto-ML features, for example, improve efficiency and speed by enabling streamlined information processing, cutting through the complexity that rigorous normalization can bring about.

Practical Solutions


Apart from Auto-ML, the Ignatius suite includes several other low-code features designed to optimize operations even further. The Public Assistance tool provides automation of tedious tasks, while the Case Management feature simplifies regulatory compliance in government administration, reinforcing the Ignatius emphasis on practicality and user-centric design.

Database management isn’t purely a science where one rule always applies. It’s an art where the best approach often depends on the requirements of the given scenario. And in the case of rapid application development, less may truly be more. is the adaptive low code platform you need to bring government and community closer together. Check out our many solutions on our website and revolutionize the way you work today.