This is the theoretical model upon which all the databases work in today’s era. So, why are we stressing more on this particular concept is because, if you understand this concept well, then not only would you be able to grasp the technical aspects in a better way, but also, you will have a great working opportunity in future if you choose a career as a database administrator. So, why were we required to develop this technology in the first place?

Because there was a very serious issue of data duplicity, you may think that, even if duplicate data occurs, so what? It can be deleted later on. But let me ask you then, what if you have the same record of data that is repeated (duplicated) 100 times? Now, if you need to change the data for that particular field in one instance, then individually, you would need to change the data for almost all 100 fields! Which is a very daunting task. Data should be precise enough without any significant redundancy (in technical terms, data duplicity is called redundancy). 

So that’s why we need a relational database model which could help us solve these real-life issues. Now, here comes another important point. If a certain record of data is repeated too many times, and it unnecessarily takes up too much space on the computer's hard disk, or if you store it in a cloud-based storage system, in both ways, your storage is wasted in some other manner. It is a waste of computational resources.

Ever wondered why we write better algorithms? Is it just to bring some newness into an already existing problem-solving technique? No. Let me explain that computational resources are very limited (since we don’t have a computer with infinitely large RAM and infinite hard disk). So that’s why we need better algorithms, and in terms of core computer science terminology, we say that we need a better time-space tradeoff. The same analogy goes in the case of databases. We require some technique that is very much efficient in managing computational resources. So, in the digital world, we are limited to such resources, and hence redundancy can cost too much.