Data Modeling with ER model
A model is an abstraction process that concentrates essential and inherent aspects of the organisation’s applications. It is a representation of the real world objects and events and their associations. A data model is a mechanism that provides this abstraction for database application. It represents the organisation itself. It provides the basic concepts and notations to allow database designers and end users unambiguously and accurately communicate their their understanding of the organisational data. Entity Relationship model is the high level conceptual model used to complete the requirements of the customers. Data modeling with ER model useful to work efficiently on the requirements of customers as Entity relationship is the high level conceptual data model.
Data Modeling with Entity Relationship Model
Data Model and It’s Classifications
A data model is a conceptual method of structuring data. It provides mechanism to structure data for the entities being modeled, allow a set of manipulative operations to be defined on them, and enforce set of constraints to ensure accuracy of data.
Types of Data Models
- Record based data models
- Object based data models
- Physical data models
Record based Data models
A record based data models are used to provide overall logical structures of the database. Here, the database consists of a number of fixed format records possibly of different types. Each record type defines a fixed number of fields, each typically of a fixed length.
Types of Record Based Data models.
- Hierarchical data model
- Network data model
- Relational data model
Object Based Data Model
Object based data models are used to describe data and its relationships. It uses concepts such as entities, attributes and relationships. It has flexible data structuring capabilities. Data integrity constraints can be explicitly specified using object based data models.
Types of Object Based Data Model
- Entity-relationship
- Semantic
- Functional
- Object oriented
Advantages of Object oriented Model
- More semantic information
- Support for complex objects
- Extensibility of data types
- Improved performance with efficient caching
- Versioning
- Faster development and easy manitainance through inheritance and reusability
- Technology driven product for next generation DBMS
- Potential to integrate DBMSs into single environment
Disadvantages of Object Oriented model
- Strong opposition from the established players
- Lack of theoretical foundation
- Retrogressive to the old pointer systems
- Lack of standard ad hoc query language
- Lack of business data design and management tools
- Steep learning curve
- Lack of resources.
Physical Data Model
Physical data models are used for a higher- level description of storage structure and access mechanism. They describe how data is stored in the computer, representing information such as records structures, record sequence and access paths. It is possible to implement the database at system level using physical data models.
The most common data models are as follows:
- (a) Unifying model
- (b) Frame memory model
Entity Relationship Model
The Entity-Relationship (ER) model is basically originated as a way to unify the network and relational database views. The ER model is a conceptual data model that views the real world as entities and relationships. A basic component of the model is the Entity-Relationship diagram, which is used to visually represent data objects.
Utilities of the ER model
The utilities of the ER model are:
(a) It maps to the relational. The constructs used in the ER model can be easily be transformed into relational tables.
(b) It is simple and easy to understand with a minimum rehearsal. Therefore ,the model can be used by the database designer to communicate the design to the end user.
(c) The model can be used as a design plan by the database developer to implement a data model in specific database management software.
Advantages of ER Data Model
- Straight forward relation representation:- Designing an ER diagram for a database application, the relational representation of the database model becomes relatively straight forward.
- Easy conversion for ER to other data model:- Conversion from ER diagram to a network or hierarchical data model can easily be done.
- Graphical representation for better understanding: An ER model gives graphical representation of various entities, its attributes and relationships between entities. This helps in a clear understanding of the data structure and in minimizing redundancy and other problems.
Disadvantages of ER data model
- No industry standard for notation: There is no industry standard notation for developing an ER diagram.
- Popular for high level design: The ER data model is especially popular for high level database design.
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