How far does one go to eliminate duplicate data in a database? Because you could go OTT and it would get crazy. Let me give you an example…
If I were to create a Zoo database which contains a table ‘Animal’ which has a ‘name’, ‘species’ and ‘country_of_birth’
But there will be duplicate data there as many animals could come from same country and there could be lots of tigers, for example.
So really there should be a ‘Species’ table and a ‘Country_of_birth’ table
But then after a while you would have tons of tables
So how far do you go?
In this question I am just using one table as an example. One row in the Animal table stores information about a single animal in the zoo. So that animal’s name, species and country of birth, as well as a unique animalID.
This suggests you want to keep track of individual animals, not just kinds of animals. Let’s assume that the zoos use some kind of numeric tattoo or microchip to identify individual animals.
Assume this sample data is representative. (It’s not, but it’s ok for teaching.)
There’s no redundant data in that table. None of those columns can be dropped without radically changing the meaning of that table. It has a single candidate key: chip_num. It’s in 5NF.
Values are repeated in non-key columns. That’s kind of the definition of non-key (non-prime) columns. Values in key columns (or sets of key columns) are unique; values in non-key columns aren’t.
If you want to restrict the values in “birth_country_code” to the valid three-letter ISO country codes, you can add a table of valid three-letter ISO country codes, and set a foreign key reference to it. This is generally a Good Thing, but it has nothing to do with normalization.
You could do the same thing again for “species”. That, too, would generally be a Good Thing, and it, too, would have nothing to do with normalization.