Well, every now and then, when we began to start a new project or app, which has some data storage requirement, we have a deep intriguing thought as to how best represent the data structure so as to support a variety of needs including but not limited to (ACID rules):
1. Normalization
2. Reliability
3. Consistency
4. And many others
Below, I provide a set of steps which you can follow to arrive at a data model that correctly suites your requirements.
Steps:
1. Identify the project or app requirements / specifications and business rules which tell you what your app will be able to do when it is ready.
2. From these business rules, identify possible objects for each business rule and mark them in a paper using rectangular sections like authors, posts etc.
3. Once you have recognized the entities and attributes, it's time to normalize the data structure and define the tables and columns.
4. After this, we now have to recognize the relationships between tables that is whether it is a one to one, one to many or many to many relationship like authors and posts have a one to many relationship.
5. Finally, we have to re-access the data model for any possible inconsistencies and refine data that is not yet normalized like any relationship with many to many relationship being moved to different tables with the help of a junction table.
So, at the end of the fifth step, we have a data model with which we can go ahead and build our database.
Now,
1. It satisfies the normalization rules
2. It represents relationships correctly between various entities taking into account the business rules of the application
3. It prevents redundancy
4. And satisfies the ACID rules
Maybe a simple theoretical explanation is not enough for we practical nerds. In a probable future post, I will explain the steps with a practical example. Stay tuned in. :)
1. Normalization
2. Reliability
3. Consistency
4. And many others
Below, I provide a set of steps which you can follow to arrive at a data model that correctly suites your requirements.
Steps:
1. Identify the project or app requirements / specifications and business rules which tell you what your app will be able to do when it is ready.
2. From these business rules, identify possible objects for each business rule and mark them in a paper using rectangular sections like authors, posts etc.
3. Once you have recognized the entities and attributes, it's time to normalize the data structure and define the tables and columns.
4. After this, we now have to recognize the relationships between tables that is whether it is a one to one, one to many or many to many relationship like authors and posts have a one to many relationship.
5. Finally, we have to re-access the data model for any possible inconsistencies and refine data that is not yet normalized like any relationship with many to many relationship being moved to different tables with the help of a junction table.
So, at the end of the fifth step, we have a data model with which we can go ahead and build our database.
Now,
1. It satisfies the normalization rules
2. It represents relationships correctly between various entities taking into account the business rules of the application
3. It prevents redundancy
4. And satisfies the ACID rules
Maybe a simple theoretical explanation is not enough for we practical nerds. In a probable future post, I will explain the steps with a practical example. Stay tuned in. :)
Designing a relational database is a critical step in building a robust and efficient data management system. How Make Career A well-structured database ensures data integrity, performance, and ease of maintenance.
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