Data Modeling

Yong ChoiSchool of Business

CSUB

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Study Objectives Understand concepts of data modeling and

its purpose Learn how relationships between entities are

defined and refined, and how such relationships are incorporated into the database design process

Learn how ERD components affect database design and implementation

Learn how to interpret the modeling symbols

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Why Data Modeling?Data Model by CASE tool = Actual

Database Represent “reality” of the actual database Blue print: documentation Effective Communication Tool User involvement Identify the business rules to be stored in

the database Independence from a particular DBMS Example of data model by CASE tool on

the website

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Conceptual data modelingConceptual data modeling

The conceptual data modeling revolves around discovering and analyzing organizational and users data requirements.

What data is important What data should be maintained

The major activity of this phase is identifying entities, attributes, and their relationships to construct model using the Entity Relationship Diagram methodology.

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Entity Relationship diagram (ERD) Entity Relationship diagram (ERD)

Data modeling methodology Developed by Peter Chen (1976).

See his original ERD article on the class website

ERD is commonly used to: Translate different views of data among managers,

users, and programmers to fit into a common framework.

Define data processing and constraint requirements to help us meet the different views.

Help implement the database.

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Basic ERD Elements

Entity : a collection of people, places, objects, events, concepts of interest (a table)

Entity instance – a member of the Entity : a person, a place, an object … (a row in a table)

Attribute - property or characteristic of interest of an entity (a field in a table)

Relationship – association between entities (corresponds to primary key-foreign key equivalencies in related tables)

Part # 2ERD using Chen’ Notation (first - original)

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Chen’s NotationChen’s Notation

Entities rectangle containing the entity’s name.

Attributes oval containing the attribute’s name.

Relationships diamond containing the relationship’s

name.

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Steps for creating an ERD

1. Identify entities2. Identify attributes 3. Identify relationships

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Entity

“A fundamental THING of relevance to the enterprise about which data may be kept”

What should be an Entity: both tangible & intangible

An object that will have many instances in the database An object that will be composed of multiple attributes An object that we are trying to model

What should NOT be an Entity: A user of the database system An output of the database system (e.g. a report)

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ERD using IE Notation (most popular)

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Entity InstanceEntity instance: a single occurrence of an entity.

6 instances

Student ID

Last Name

First Name

2144 Arnold Betty

3122 Taylor John

3843 Simmons Lisa

9844 Macy Bill

2837 Leath Heather

2293 Wrench Tim

Entity: student

instance

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13

“describe property or characteristic of an entity ” Entity: Employee Attributes:

Employee-Name Address (composite) Phone Extension Date-Of-Hire Job-Skill-Code Salary

AttributesAttributes

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Classes of attributes

Simple attribute Composite attribute Derived attributes Single-valued attribute Multi-valued attribute

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A simple attribute cannot be subdivided. Examples: Age, Gender, and Marital status

A composite attribute can be further subdivided to yield additional attributes. Examples:

ADDRESS -- Street, City, State, Zip PHONE NUMBER -- Area code, Exchange

number

Simple/Composite attributeSimple/Composite attribute

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is not physically stored within the database instead, it is derived by using an algorithm.

Example: AGE can be derived from the date of birth and the current date.

MS Access: int(Date() – Emp_Dob)/365)

Derived attributeDerived attribute

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“attributes that uniquely identify entity instances” Uniquely identify every instance of the entity One or more of the entity’s attributes

Composite identifiers are identifiers that consist of two or more attributes

Identifiers are represented by underlying the name of the attribute(s)Employee (employee_ID), student (student_ID)

(unique) Identifier(unique) Identifier

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Type of Relationships

One – to – One (1:1) Each instance in the relationship will have exactly one

related member on the other side One – to – Many (1:M)

A instance on one side of the relationship can have many related members on the other side, but a member on the other side will have a maximum of one related instance

Many – to – Many (M:N) Instances on both sides of the relationship can have many

related instances on the other side

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1:1 relationship in Set notation

DEPARTMT EMPLOYEE

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1:M relationship in Set notation

DEPARTMT EMPLOYEE

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M:N relationship in Set notation

WAREHOUSE PRODUCT

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M:N relationship

Each student takes many classes, and a class must be taken by many students.

** Many-to-many relationships cannot be used in the data model because they cannot be represented by the relational model (see the next slide for the reason) **

STUDENTCLASSTAKE

IS_TAKEN_BY

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Example of M:N

Many-to-many relationships is a second sign of complex data.

When x relates to many y's and y relates to many x's, it is a many-to-many relationship.

In our example schema, a color swatch can relate to many types of sweaters and a type of sweater can have many color swatches. 

Part # 2Example M:N Relationship

3 to 330 to 30

300 to 3003000 to 3000

30,000 to 30,000300, 000 to 300, 000

Table to represent Entity

Part # 2Converting M:N Relationship to Two 1:M Relationships

Bridge Entity

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Bridge Entity

MUST have a composite (unique) identifier STU_NUM (from STUDENT entity) and CLASS_CODE

(from CLASS entity)