Database design is a crucial aspect of building any software application that requires the storage and management of data. A well-designed database can ensure data integrity, efficient access to information, and scalability for future growth. In this blog post, we will cover several key concepts in database design, including its definition, mapping an Entity-Relationship (ER)/Enhanced ER (EER) model to a relational database, why database design is important, process of database design, functional dependencies, lossless decomposition, and normal forms up to Boyce-Codd Normal Form (BCNF).
What is Database Design?
Database design can be generally defined as a collection of tasks or processes that enhance the designing, development, implementation, and maintenance of enterprise data management system. Designing a proper database reduces the maintenance cost thereby improving data consistency and the cost-effective measures are greatly influenced in terms of disk storage space. Therefore, there has to be a brilliant concept of designing a database. The designer should follow the constraints and decide how the elements correlate and what kind of data must be stored.
The main objectives behind database designing are to produce physical and logical design models of the proposed database system. To elaborate this, the logical model is primarily concentrated on the requirements of data and the considerations must be made in terms of monolithic considerations and hence the stored physical data must be stored independent of the physical conditions. On the other hand, the physical database design model includes a translation of the logical design model of the database by keep control of physical media using hardware resources and software systems such as Database Management System (DBMS).
Why Database Design is important?
The important consideration that can be taken into account while emphasizing the importance of database design can be explained in terms of the following points given below.
Data Integrity: A well-designed database ensures data integrity, which means that the data stored in the database is accurate, consistent, and complete.
Efficient Access: Efficient access to data is essential for the smooth functioning of any software application. Proper database design ensures that data can be retrieved quickly and easily.
Scalability: A well-designed database can scale with the needs of the application. As the application grows, the database can be expanded without any major redesign.
Reduced Redundancy: Proper database design reduces data redundancy, which means that the same data is not stored in multiple places. This leads to a more efficient use of storage space and less chance of data inconsistencies.
Consistency: Consistency in data is crucial, and a well-designed database ensures that the data is consistent across all tables and fields.
Security: Proper database design ensures that the data is secure and cannot be accessed by unauthorized users.
Future Proofing: By designing a database with future growth in mind, you can avoid the need for major redesigns or migrations down the line.
Collaboration: Database design is often a collaborative process between developers, DBAs, and other stakeholders. By working together on the design, everyone can be on the same page and ensure that the database meets the needs of the application.
Database Design Process
The process of designing a database carries various conceptual approaches that are needed to be kept in mind. An ideal and well-structured database design must be able to:
Save disk space by eliminating redundant data.
Maintains data integrity and accuracy.
Provides data access in useful ways.
Comparing Logical and Physical data models.
Mapping ER/EER Model to Relational Database:
Entity-Relationship (ER) and Enhanced Entity-Relationship (EER) models are used to design a conceptual schema of a database. In these models, entities represent real-world objects or concepts, and relationships between entities depict the association between them. A relational database is based on tables that consist of rows and columns.
The mapping of an ER/EER model to a relational database involves converting entities into tables and relationships into foreign key constraints. Each attribute of an entity becomes a column in a table, and the primary key of the entity becomes the primary key of the corresponding table. The relationship between two entities is implemented by adding a foreign key column in the table of the entity that is on the many-side of the relationship.
Functional dependencies are a key concept in database design that describe the relationship between attributes in a table. A functional dependency exists when the value of one attribute determines the value of another attribute. For example, if we have a table of customer information that includes the attributes ‘CustomerID,’ ‘Name,’ and ‘Email,’ the attribute ‘CustomerID’ determines the values of ‘Name’ and ‘Email.’
Functional dependencies are denoted by an arrow symbol ‘→.’ In the above example, we write ‘CustomerID → Name, Email’ to indicate that the value of ‘CustomerID’ determines the values of ‘Name’ and ‘Email.’ Functional dependencies play a crucial role in determining the normal forms of a database.
Decomposition is the process of splitting a table into two or more tables to eliminate redundancy and improve data consistency. However, the decomposition should be lossless, meaning that the original data can be reconstructed from the decomposed tables without losing any information.
A lossless decomposition is achieved by ensuring that the common attributes of the original table are preserved in the decomposed tables. This is done by adding the primary key of the original table to each of the decomposed tables and making it a foreign key. This ensures that the relationship between the tables is preserved and that no information is lost during the decomposition process.
Normal forms are a set of rules that determine the level of data redundancy and data dependencies in a database. There are several normal forms, and each normal form is a stricter set of rules than the previous one. The most commonly used normal forms are First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and Boyce-Codd Normal Form (BCNF).
1NF: A table is in 1NF if it contains only atomic values, meaning that each column contains only one value.
2NF: A table is in 2NF if it is in 1NF and each non-key attribute is dependent on the entire primary key, not just a part of it.
3NF: A table is in 3NF if it is in 2NF and there are no transitive dependencies, meaning that if A → B and B → C, then A does not determine C.
BCNF: A table is in BCNF if it is in 3NF and every determinant is a candidate key. In other words, no non-key attribute is functionally dependent on a subset of the primary key.
In conclusion, database design is a process that involves mapping an ER/EER model to a relational database, ensuring functional dependencies, performing lossless decomposition, and achieving normal forms up to BCNF. A well-designed database is essential for ensuring data integrity, efficient access to information, and scalability for future growth. By following these principles, you can ensure that your database is robust, efficient, and can meet the needs of your software application. So, take the time to design your database carefully, and you’ll reap the benefits of a smooth and successful application.