What do you mean by data normalization?

Data normalization is a process in database design that organizes data to minimize redundancy and avoid data anomalies. It involves decomposing a table into less redundant (and smaller) tables but without losing information; defining foreign keys in the old table referencing the primary keys in the new ones. The objective is to isolate data so that additions, deletions, and modifications of a field can be made in just one table and then propagated through the rest of the database via the defined foreign keys.

Here are the steps involved in normalizing data:

1. First Normal Form (1NF): In this step, the database table is organized in such a way that each column contains atomic (indivisible) values and there are no repeating groups. Each entry has a unique identifier or primary key.

2. Second Normal Form (2NF): In this step, the database table is organized to remove partial dependencies, i.e., all non-key attributes should be fully functionally dependent on the primary key.

3. Third Normal Form (3NF): In this step, the database table is organized to remove transitive dependencies. A table is in 3NF if it is in 2NF and no non-key attribute is dependent on any other non-key attribute.

4. Boyce-Codd Normal Form (BCNF): This is a stronger version of the 3NF. A table is in BCNF if, and only if, for every one of its dependencies X → Y, X is a superkey.

5. Fourth Normal Form (4NF): In this step, the database table is organized to remove multi-valued dependencies.

6. Fifth Normal Form (5NF): In this step, the database table is organized to remove join dependencies.

The normalization process brings order to your filing cabinet, allowing the database to manage, store and retrieve information in the most efficient and flexible way possible.