Data Modeling

Conceptual Data Modeling

4. Data Modeling 

4.1 Conceptual Data Modeling

      4.1.1 Introduction to Conceptual Data Model
      4.1.2 Stages in Conceptual Modeling
      4.1.3 Components of a Conceptual Data Model
      4.1.4 ER Modeling Basic Concepts
      4.1.5 Enhanced ER Modeling
      4.1.6 Guidelines for ER Modeling

4: 4.1 Conceptual Data Model

Conceptual Data Model 

A conceptual schema or conceptual data model is a map of concepts and their relationships. This describes the semantics of an organization and represents a series of assertions about its nature. Specifically, it describes the things of significance to an organization (entity classes), about which it is inclined to collect information, and characteristics of (attributes) and associations between pairs of those things of significance (relationships).

A conceptual data model identifies the highest-level relationships between the different entities. 

Features of conceptual data model include: 

Includes the important entities and the relationships among them. 
No attribute is specified. 
No primary key is specified. 

4.1.2 Stages in Conceptual Modeling

Main stages in conceptual modeling are as follows:

--  Identification of requirements (done in previous lesson)
--  Designing of solutions
--  Evaluation of solutions

4.1.3 Components of a Conceptual Data Model

  

4.1.4 ER Modeling Basic Concepts

ER Model

The ER model is a conceptual model
Describes data as entities, relationships and attributes
No standard notation for displaying ER diagrams 
(We will choose one among several alternatives for this presentation)

Entity

An entity is a “thing” in the real world with an independent existence
An entity may be an object with a physical existence
For example, person, car, house
An entity may be an object with a conceptual existence
For example, company, job, university-course

4.1.5 Enhanced ER Modeling

  

Enhanced ER Model, Includes all the modeling concepts of the ER model

In addition, it includes the following concepts:

• Subclass & super-class
• Specialization & generalization
• Category
• Attribute & relationship inheritance

Subclass & Super-class

• In many cases an entity type has numerous sub-groupings of its entities that are meaningful and need to be represented explicitly because of their significance to the database application. Each of these sub-groupings are called subclass.
• The entity type on which these subclasses are formed is called super-class
• The relationship between a super-class and any one of its subclasses is called a super-class/subclass, a class/subclass or an IS-A (or IS-AN) relationship, e.g., a SECRETARY IS-AN EMPLOYEE
• A member entity of a subclass represents the same real-world entity as some member of the super-class, but in a distinct specific role

Specialization (Top to Bottom Approach)

Specialization is the process of defining a set of subclasses of an entity type

In addition, it allows us to do the following:

•  Establish additional specific attributes with each subclasses
•  Establish additional specific relationship types between each subclass and other entity types or other subclasses

Logical Data Modeling

Introduction to Logical Model

Logical Data Model refers to the actual implementation of a conceptual module in a database. It represents normalized design of common data model which is required to support the design of an information system. The very core of the logical data model is the definition of the three types of data objects which the building blocks of the data model and these data objects are the entities, attributes, and relationships. Entities refer to persons, places, events or things which are of particular interest to the company.

Some examples of entities are Employees, States, Orders, and Time Sheets. Attributes refer to the properties of the entities. Examples of attributes for the Employee entity are first name, birthday, gender, address, age and many others. Lastly, relationships refer to the way where in the entities relate to each other.  An example relationship would be "customers purchase products" or "students enroll in classes".  

If the database is ported to another DBMS supporting a similar structure, the logical data model can still be used as a baseline for the new physical data model.


Characteristics of a Logical Model

• Logical model works in an iterative manner.
• Its design is independent of database.
• It includes all entities and relationships among them.
• All attributes for each entity are specified.
• The primary key for each entity is specified.
• Foreign keys (keys identifying the relationship between different entities) are specified.
  
  






Physical Data Modeling

Physical Database Design

Physical database design is the process of developing a set of required data structures on a selected database. It involves the following tasks: 

• Converting entities into tables
• Converting relationships into foreign keys
• Converting attributes into columns
• Defining constraints
 The purpose of physical design is to optimize performance as closely as possible.








 Along with the logical data model, the database designer requires the following to make sound design decisions:


• The Process Model, detailing input processes (creation and updating of rows in tables) and output requirements (retrieval of data from the database)
• The mapping that shows the processes that access each entity class and how (create, update, retrieve)
• Nonstructural data requirements
• Performance requirements
• The target DBMS
• Disk space requirement
• Availability of skilled programming resources