2. Relational Model Relational model is based on first-order predicate logic. This model was first proposed by E. F. Codd. It represents data as relations or tables. Relational database simplifies the database structure by making use of tables and columns. 3. Network Database Model Network Database Model is same like Hierarchical Model, but the only difference is that it allows a record to have more than one parent. In this model, there is no need of parent to child association like the hierarchical model. It replaces the hierarchical tree with a graph. It represents the data as record types and one-to-many relationship.
This model is easy to design and understand. 4. Entity Relationship Model Entity Relationship Model is a high-level data model. It was developed by Chen in 1976. This model is useful in developing a conceptual design for the database. It is very simple and easy to design logical view of data. The developer can easily understand the system by looking at an ER model constructed. In this diagram, Rectangle represents the entities. Eg. Doctor and Patient. Ellipse represents the attributes. Eg. DocId, Dname, PId, Pname. Attribute describes each entity becomes a major part of the data stored in the database. Diamond represents the relationship in ER diagrams. Eg. Doctor diagnoses the Patient.
5. Object Model Object model stores the data in the form of objects, classes and inheritance. This model handles more complex applications, such as Geographic Information System (GIS), scientific experiments, engineering design and manufacturing. It is used in File Management System. It represents real world objects, attributes and behaviors. It provides a clear modular structure. It is easy to maintain and modify the existing code.
Database Normalization Introduction to Normalization Normalization is a process of organizing the data in the database. It is a systematic approach of decomposing tables to eliminate data redundancy. It was developed by E. F. Codd. Normalization is a multi-step process that puts the data into a tabular form by removing the duplicate data from the relation tables. It is a step by step decomposition of complex records into simple records. It is also called as Canonical Synthesis. It is the technique of building database structures to store data. Definition of Normalization “Normalization is a process of designing a consistent database by minimizing redundancy and ensuring data integrity through decomposition which is lossless.” Features of Normalization Normalization avoids the data redundancy. It is a formal process of developing data structures. It promotes the data integrity. It ensures data dependencies make sense that means data is logically stored. It eliminates the undesirable characteristics like Insertion, Updation and Deletion Anomalies.