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Data modelling, compare Data models | RGPV DBMS PYQ

RGPV 2019
Q. What do you mean by data modelling ? Compare different data models ?

Ans. Data modeling is a way to create data model for the data to be stored in a database. 
A data model a collection of conceptual tools for describing data, data relationships, data semantics, and consistency constraints. A data model provides a way to describe the design of a database at the physical, logical, and view levels.

Feature

Conceptual

Logical

Physical

Entity names

Entity relationships

Primary keys

 

Foreign keys

 

Column names

 

 

Column data types

 

 

The data models can be classified as:
  1. Relational Model
  2. Entity-Relationship Model.
  3. Object-Based Data Model
  4. Semi-structured Data Model
  5. Network Data Model
  6. Hierarchical Data Model
1. Relational model: 
  • The relational model uses a group of tables to represent both data and the relationships amongst those records. 
  • Each table has more than one column, and each column has a unique name. Tables are also referred as relations. 
  • Each table contains records of a specific type. Each record type defines a fixed number of fields, or attributes. 
  • The columns of the table correspond to the attributes of the record type. 
  • The relational data model is the most widely used data model.
2. Entity-Relationship Model:
  • The entity-relationship (E-R) data model uses a collection of basic objects, called entities, and relationships among these objects.
  • An entity is a “thing” or “object” in the real world that is distinguishable from other objects.
3. Object-Based Data Model:
  • Object-oriented programs (especially in Java, C ++, or C #) have become the preferred method of software development.
  • This has led to the development of an object-focused data model that can be seen as an extension of the ER model with input ideas, methods (functions), and object.
  • An object-related data model incorporates features of an object-focused data model and a data-related data model.
4. Semi-structured Data Model:
  • The semi-structured data model permits the specification of data in which individual data items of the same type may have different sets of attributes. 
  • This is in contrast to the data models mentioned earlier, in which every data item of specific type must have the identical set of attributes. 
  • Extensible Markup Language (XML) is extensively used to represent semi-structured data.
5. Network Data Model:
  • A network data model is a data model that allows multiple records to be linked to the same owner.
  • The model can be seen as an upside down tree wherein the branches are the member information connected to the owner, that is the lowest of the tree.
  • The multiple linkages which this information permits the network data model to be very flexible. 
  • Further, the relationship that the information has within the network data model is defined as many-to-many relationship because one owner file may be linked to many member documents and vice versa.
6. Hierarchical Data Model:
  • Hierarchical Data Model involves parent/child relationship.
  • In Hierarchical Data Model, parent can have more than one child.
  • In Hierarchical Data Model, child can have only parent.
  • Hierarchical data model visualize as upside/down tree.