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DATA MODELLING

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A database designer initially represent high-level database design

that is understood by the users and then translate therequirements into lower levels of the design

A high level data model serves the database designer byproviding a conceptual framework in which to specify, in asystematic fashion, the data requirements of the database users,and a database structure that fulfills these requirement

Initial Phase: the database designer needs to interact extensively with

domain experts and users to carry out this task

The outcome of this phase is a specification or userrequirements

Conceptual Design: Next, designer, by applying the concepts of the chosen data

model, translates these requirements into conceptual schema ofthe database

The schema developed at the conceptual-design phaseprovides a detailed overview of the enterprise

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The process of moving from an abstract data model to the

implementation of the database proceeds in two steps:

The logical design phase The designer maps thehigh-level conceptual schema onto theimplementation data model of the database system

that will be used. The implementation data model is typically the

relational data model, and this step typicallyconsists of mapping the conceptual schema definedusing the entity-relationship model

Physical-design phase- Physical features of thedatabse are specified. These features include theform of file organization and the internal storagestructures

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Data flow diagram and various processing logicaltechniques show how, where, and when data are used orchanged in an information system, but these techniques donot show the definition, structure, and relationships withinthe data.

Data modeling is a technique for organizing anddocumenting a systems data. Data modeling is sometimescalled database modeling because a data model iseventually implemented as a database. It is sometimes

called information modeling.

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The entity relationship model (E-R) was developed to

facilitate database design by allowing specification ofan enterprise schema that represents the overall logicalstructure of a database

The E-R model is very useful in mapping the meanings

and interactions of real-world enterprises onto aconceptual schema

The E-R model employs three basic notations:

Entity Set

Relationship sets and Attributes

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Developers believe that a data model is the most important

part of the information system requirements because: First, the characteristics of data captured during data

modeling are crucial in the design of databases, programs,computer screens, and printed reports.

Second, data rather than processes are the most complexaspects of many modern information systems and hencerequire a central role in structuring system requirements.

The goal is to provide a rich data resource that mightsupport any type of information inquiry, analysis, andsummarization.

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ERD do not depict flow or processing. They should not be

read like data flow diagrams or flowcharts. ERD depict data at rest, data being stored. They also do

not imply how data is implemented created, modified,used or deleted.

There are several notations for data modeling. The actualmodel is frequently call an Entity Relationship

Diagram(ERD) because it depicts data in terms of theentities and relationships described by the data.

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Entity

An entity is anything, real or abstract, about which wewant to store data. Synonyms include Entity Typeand Entity Class

For any given entity, the real world will contain

multiple occurrences of that entity. Most entitiescorrespond to persons, objects events or location inthe business environment

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Entity

Name

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Attributes: An attribute is a descriptive property or

characteristics of an entity. Synonyms include element,property and field e.g.Entity : Student

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STUDENT

Name

.Last Name

.First Name

.Middle InitialAddress

.Street Address

.City

.State or Province

.Country

.Postal CodePhone Number.Area Code

.Exchange Number

.Number Within ExchangeDate of BirthGender

RaceMajorGrade Point Average

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A key is an attribute, or a group of attributes, that assumes a

unique value for each entity instanceCANDIDATE KEY is a candidate to become the primary

identifier of instances of an entity.

ALTERNATE KEY : Any candidate key that is not selected to

become the primary key is called an alternate key.SECONDARY KEY is an attribute or combination of attributes

that may not be a candidate key but that classifies the entity

set on a particular characteristic.

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.

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A relationship is a natural business association thatexists between one or more entities. The relationshipmay represent an event that links the entities or merelya logical affinity that exists between the entities.

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bidirectional

Car i alit efi es t e i i and maximumnumber f ccurrences f ne entit t at may be relatedt a single ccurrence f t e t er entity.

Because all relati ns i s are bidirecti nal, cardinalitymust be defined in bot directions for e ery

relations i .

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All Relationships are further described by words or symbols

that indicate the number of occurrences of one entity that canexist for a single occurrence of the related entity and viceversa. There are three general possibilities :

One-to-one(1:1) : For one occurrence of the first entity therecan exist only one related occurrence of the second entity and

vice versaOne-to-Many (1:M or M:1) : For one occurrence of one entitythere can exist many related occurrences of a second entity

Many to Many (M:M) : For one occurrence of the first entity,there can exist many related occurrences of the second entityand for one occurrence of the second entity there can existmany occurrences of the first entity

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The degree of a relationship is the number of entitiesthat participate in the relationship.

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A recursive relationship is a relationship that exists

between different instances of the same entity

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