Data Model: A data model is defined as a set of concepts for describing the structure of the database. Database structure comprises of data types, relationships, constraints applied to the data and basic operations for accessing the data.
Data models are classified as follows:
Conceptual Data Model: It is an abstract-level or summary-level data model. It is used in strategic data projects. It uses high-level key concepts that are easy to understand by end user and very close to the way of how end user see data in an enterprise or an organization.
Following high-level concepts are used:
Entities: A real-world object, such as an student, course, teacher etc.
Attributes: Property of an entity, such as student name, date of birth, gender, etc. Conceptual level defines extremely limited number of attributes in a model.
Relationships: Association between two or more entities. For example an student is enrolled in a course.
- ER Model: The most popular and widely used model in database designing. It is a way of graphically expressing the entities, attributes and relationships by an E-R (Entity-Relationship) diagram. In E-R diagram entities are represented as rectangle, attributes are represented as ellipses, relationship between entities are represented as diamond and lines are used to link attributes to entity and entity to relationship.

- Object Based Data Model: There are two object based data model, Object Oriented Data Model and Object Relational Data Model. Object oriented data model is based on the object oriented concepts like object identity, encapsulation, methods etc. used by object oriented programming languages like C++ and Java. An object is a real world entity that has state and behavior. Object oriented database enables permanent storage of objects in database. These objects then act as persistent objects and exist after program termination, so that they can be accessed later and shared by other programs. Relational model with the enhancements of object oriented data model is known as object relational model.
Representational Data Model: This model is also known as Record Based Data Model. These models generally represents the record structure.
- Relational Model: Represents data and relationship between data using the concept of tables. Tables consist of columns with unique names and rows. Table is also known as relation. A column corresponds an attribute and a row represents a record that typically corresponds to a real-world entity or relationship.
- Hierarchical Model: Data model that links record in a tree data structure in such a way that every record has only one owner. This tree is known as database tree. A tree structure diagram represents schema for a hierarchical database, in which boxes corresponds to record type and line corresponds to links. This model is more efficient when database contains a large number of 1:N (one-to-many) relationships.
- Network Model: This model is based on directed graph theory. Instead of hierarchical tree it uses graphs and provides more generic connections among the nodes. Similar to hierarchical model it uses boxes and line to represent record and links respectively. It has the ability of handling N:N relationships (many-to-many) that means it allows to have more than one parent.
Physical Data Model: In this model describes how data is stored in a file in a physical storage. It also represents information like record formats, record orderings and access paths.
- Index: Index is used to define the efficient access paths for fast access of data from database systems. Indexes are usually written on primary attributes (that has unique value).
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