11 Important Database Designing Rules

One of the solutions would be to move the data into a different master table altogether and refer them via foreign keys. You can see in the below figure how we have created a new master table called "Standards" and linked the same using a simple foreign key.

Rule 5. Watch for data separated by separators

The second rule of 1st normal form says to avoid repeating groups. One of the examples of repeating groups is explained in the below diagram. If you see the syllabus field closely, we have too much data stuffed in one field. These kinds of fields are termed "Repeating groups." If we have to manipulate this data, the query would be complex, and I doubt the performance of the queries.

These kinds of columns with data stuffed with separators need special attention, and a better approach would be to move that field to a different table and link the same with keys for better management.

So now let's apply the second rule of 1st normal form "Avoid repeating groups." In the above figure, I created a separate syllabus table and then made a many-to-many relationship with the subject table.

With this approach, the syllabus field in the main table is no more repeated and has data separators.

Rule 6. Watch for partial dependencies

Watch for fields which are depending partially on primary keys. For instance, in the above table, we can see the primary Key is created on roll number and standard. Now watch the syllabus field closely. The syllabus field is associated with a standard and not with a student directly (roll number).

A syllabus is associated with the standard in which the student is studying and not directly with the student. So if tomorrow we want to update the syllabus, we have to update it for each student, which is painstaking and not logical. Moving these fields out and associating them with the standard table makes more sense.

You can see how we have moved the syllabus field and attached the same to the standards table.

This rule is nothing but the second normal form "All keys should depend on the full primary key and not partially."

Rule 7. Choose derived columns preciously

If you are working on OLTP applications, getting rid of deriving columns would be a good thought until there is some pressing reason for performance. In the case of OLAP, where we do a lot of summations and calculations, these fields are necessary to gain performance.

In the above figure, you can see how the average field is dependent on marks and subject. So for such kinds of areas derived from other fields, think about whether they are essential. This is also one form of redundancy.

This rule is also called the 3rd normal form "No columns should depend on other non-primary key columns." My thought does not to apply this rule blindly to see the situation; it's not that redundant data is always wrong. If the redundant data is calculative data, see the situation and decide if you want to implement the third normal form.

Rule 8. Do not be hard on avoiding redundancy, if performance is the Key

Do not make it a strict rule that you will always avoid redundancy. If there is a pressing need for performance, think about denormalization. In normalization, you need to make joins with many tables, and in denormalization, the joins reduce and thus increase performance.

Rule 9. Multidimensional data is a different beast altogether

OLAP projects mainly deal with multidimensional data. For instance, you can see the figure below; you would like to get sales per country, customer, and date. Simply put, you are looking at sales figures with three intersections of dimension data.

For such situations, a dimension and fact design is a better approach. Simply put, you can create a central sales fact table with the sales amount field, and he connects all dimension tables using a foreign key relationship.

Rule 10. Centralize name value table design

Many times I have come across name-value tables. Name and value tables mean it has a key and some data associated with the Key. For instance, in the figure below, we have a currency table and a country table. If you watch the data closely, they only have Key and value.

Creating one central table and differentiating the data by using a type field makes more sense for such kind of table.

Rule 11. For unlimited hierarchical data self-reference PK and FK

Many times we come across data with an infinite parent-child hierarchy. For instance, consider a Multi-level marketing scenario where one salesperson can have multiple salespeople below them. Using a self-referencing primary and foreign key for such systems will help achieve the same.

This article is not meant to say that do not follow normal forms but do not follow them blindly, look at your project's Nature and the type of data you are dealing with.

Conclusion

This article taught us about 11 crucial database design rules in detail. Happy reading.