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Conceptual Modelling using ERD(with focus on Chen Notation)
Lesson 3
2
Lesson Outcomes
At the end of the lesson, students should be able to :• Conceptually depict a database structure in an ER Diagram
(using Chen Notation)• Identify and describe the main characteristics of ERD’s
components such as – Entity– Attributes
• Identifier attributes (Keys) – Primary/Composite/Foreign
• Composite and simple attributes
• Single-valued and Multivalued attributes
– Relationships• Connectivity & cardinality
• Degree of relationship
PRODUCT CUSTOMER
SUPPLIER
purchasedBy
suppliedBy
m n
1
m
prodID
name
price qtyBoughtcustID
name
contactNo
suppID
name address
contactNo
4
Intro to Modeling
• In the programming env., a problem that needs to be solved must be critically analyze first before a solution can be designed.
• In programming, the analysis will identify (1) the inputs (2) the outputs (3) the process
• After that an approach to solve the problem will be selected, e.g., procedural/structured, object-oriented, logical etc.
• Then, if for example, structured approach is selected, then the solution will be designed using certain model, e.g., flowchart, pseudocode, etc.
5
Intro to Modeling – cont’d
• After that only the actual coding will be done using certain programming language, e.g., C.
• The C compiler itself can be provided by many publishers such as Turbo C, Borland C, etc.
6
Intro to Entity Relationship (ER) Model• The same concept applies in database development
• In the database env., a problem that needs to be solved must be critically analyze first before a solution can be designed. (Here the problem is to keep storage of data for later use)
• The analysis will identify (1) the structure of the storage (2) the transactions/operations to be done
• Then, the solution will be depicted using certain model, e.g., ER, UML – For structure : ER Diagram, UML Class Diagram, etc.– For transaction: relational algebra, etc.
7
Entity Relationship (ER) Model – cont’d
• After that a solution will be refined using certain approach, e.g., relational, object-oriented, network, hierarchical, etc.
• After that only the actual coding will be done using database language called Structured Query Language (SQL).
• Again SQL is supported by many database software, e.g., Oracle, MySQL, Informix, SQL Server, etc.
8
Entity Relationship (ER) Model – cont’d
Database Structure Modeling using ERD
• ERD is a pictorial representation of a database structure. Different shapes of items in the diagram represents different components of the database. – Entities– Attributes– Relationships
• There are many variations in terms of the shapes. The popular ones are based on Chen and Crow foot notations.
One-to-One One-to-Many Many-to-Many
CUSTOMER ACCOUNT STUDENT COURSE
1 1 1 M M N
STUDENT
STUDENT
STUDENT
STUDENT
1
2
3
4
5
COURSE
COURSE
COURSE
COURSE
CUSTOMER
CUSTOMER
CUSTOMER
CUSTOMER
ACCOUNT
ACCOUNT
ACCOUNT
ACCOUNT
EMPLOYEE
EMPLOYEE
EMPLOYEE
EMPLOYEE
EMPLOYEE
TEMP_EMP
TEMP_EMP
TEMP_EMP
TEMP_EMP
TEMP_EMP
Variation in ER Model
(1) Ross, (2) Bachmann, (3) Martin (crow foot), (4) Chen, (5) Rumbaugh.
Person, place, object, event or concept about which data is to be maintained
named property or characteristic of an entity
Association between the instances of one or more entity types
Represents a set or collection of objects in the real world that share the same properties
EntityName Verb Phrase AttributeName
Chen Notation
11
Entities
• Refers to entity set and not to single entity occurrence
• Corresponds to table and not to row in relational environment
• In both Chen and Crow’s Foot models, entity is represented by rectangle containing entity’s name
• Entity name, a noun, is usually written in capital letters
Entities – cont’d
• Examples of entities:– Person: EMPLOYEE, STUDENT, PATIENT– Place: STORE, WAREHOUSE– Object: MACHINE, PRODUCT, CAR– Event: SALE,REGISTRATION, RENEWAL– Concept: ACCOUNT, COURSE
• Guidelines for naming and defining entity types:– An entity type name is a singular noun– An entity type should be descriptive and specific – An entity name should be concise– Event entity types should be named for the result of the event, not
the activity or process of the event.
13
Attributes
• Characteristics of entities
• In Chen model, attributes are represented by ovals and are connected to entity rectangle with a line
• Each oval contains the name of attribute it represents
• In Crow’s Foot model, attributes are written in attribute box below entity rectangle (oval also acceptable)
Attributes – cont’d
• Example of entity types and associated attributes:STUDENT: Student_ID, Student_Name, Home_Address,
Phone_Number, Major
• Guidelines for naming attributes:– An attribute name is a noun.
– An attribute name should be unique
– To make an attribute name unique and clear, each attribute name should follow a standard format
– Similar attributes of different entity types should use similar but distinguishing names.
15
Composite vs Simple Attributes
• Attributes can be simple OR composite• Composite attribute (NOT composite key) can be
subdivided to yield additional attributes. – an ADDRESS attribute can be subdivided into city,
state and postcode– NAME attribute can be subdivided into first_Name
and Last_Name• Simple attribute cannot be subdivided.
Ex. AGE, MARITAL STATUS
16
Composite vs Simple Attributes
STUDENT
age name
fname
lname
Simple attribute
Composite attribute
17
Single-Valued vs Multivalued Attributes
• Single-value attribute can have only a single value
Ex. CAR_MODEL_NO
• Not necessarily a simple attribute
Ex. IC_NUM => 780417-08-5284
is a composite attribute because it can be subdivided into birthdate (780417), place of birth (08), serial number (5284)
Multivalued attributes can have many values
Ex. A car color may be subdivided into many colors (colors for the roof, body and trim)
Chen Model, the multivalued attributes are shown by double line connecting the attribute to the entity.
ERD :: 19 / 1 / 07 18
18
Multivalued Attributes (continued)
19
Resolving Multivalued Attribute Problems
• Although conceptual model can handle multivalued attributes, you should not implement them in relational DBMS
– Option 1: Within original entity, create several new attributes, one for each of the original multivalued attribute’s components
• Can lead to major structural problems in table
– Option 2: Create new entity composed of original multivalued attribute’s components
ERD :: 19 / 1 / 07 20
20
Resolving Multivalued Attribute Problems (continued)
Option 1: Within original entity, create several new attributes
ERD :: 19 / 1 / 07 21
21
Resolving Multivalued Attribute Problems (continued)
Option 2: Create new entity composed of original multivalued attribute’s components
Identifier vs non-identifierAttributes
• Non-identifier– Attribute which is not unique among instances of an entity
• Candidate key– Attribute (or combination of attributes) that uniquely identifies
each instance of an entity type
– Some entities may have more than one candidate key• Ex: A candidate key for EMPLOYEE is Employee_ID, a second is the
combination of Employee_Name and Address.• If there is more than one candidate key, need to make a choice.
• Identifier/primary key– A candidate key that has been selected as the unique identifying
characteristic for an entity type
Example
Staff
StaffID
Name Gender
IC
Staff
StaffID
NameGenderIC
PK
Chen Notation
Crow’s Foot Notation
Referential/foreign key Attributes
Name IdNum DeptID Email
Ali 105 LG ali@a.com
Mary 106 IT mary@a.com
John 107 ENG john@a.com
Lim 108 IT lim@a.com
Name IdNum DeptID Email
Ali 105 LG ali@a.com
Mary 106 IT mary@a.com
John 107 ENG john@a.com
Lim 108 IT lim@a.comInstance of Lecturer.
Referential attribute: Ties the lecturer entity to another entity that is department.
• Make Reference to another instance in another table
25
Derived Attributes
• Attribute whose value may be calculated (derived) from other attributes.
Ex. EMP_AGE can be derived by computing the difference between the current date and the EMP_DOB
• Need not be physically stored within database.• Can be derived by using an algorithm.• Chen Model, the derived attribute is connected to the
entity using dashed line.
Relationships
Associations between instances of one or more entity types that is of interest
Given a name that describes its function.
• relationship name is an active or a passive verb.
Associations between instances of one or more entity types that is of interest
Given a name that describes its function.
• relationship name is an active or a passive verb.
Author Book
Relationship name: writes
An author writes one or more booksA book can be written by one or more authors.
Degree of Relationships
• Degree: number of entity types that participate in a relationship
• Three cases– Unary: between two instances of one entity type– Binary: between the instances of two entity types– Ternary: among the instances of three entity types
Cardinality and Connectivity
• Relationships can be classified as either • one – to – one• one – to – many• many – to –many
• Cardinality : minimum and maximum number of instances of Entity B that can (or must be) associated with each instance of entity A.
Connectivity
Cardinality and Connectivity
Professor Classteaches
A professor teaches class ORA class is taught by professor
How Many??How Many??
Professor Classteaches
Cardinality and Connectivity
Professor Classteaches
Professor Classteaches
1 M
Connectivity
Connectivity
(1,1)
(1,1)
(1,4)
(1,4)
Cardinality
Cardinality
• Chen Model– 1 to represent one. – M to represent many
• Crow’s Foot
Connectivity
many
One
One or many
1
M
Mandatory one , means (1,1)
Optional? – we’ll see after this
Binary Relationships
• 1:M relationship
– Relational modeling ideal
– Should be the norm in any relational database design
The 1: M relationship between PAINTER and PAINTING
The Implemented 1:M relationship between PAINTER and PAINTING
Binary Relationships
• 1:1 relationship – Should be rare in any relational database design
– A single entity instance in one entity class is related to a single entity instance in another entity class
– Could indicate that two entities actually belong in the same table
The 1:1 Relationship Between PROFESSOR and DEPARTMENT
The Implemented 1:1 Relationship Between PROFESSOR and DEPARTMENT
Binary Relationships
• M:N relationships
– Must be avoided because they lead to data redundancies.
– Can be implemented by breaking it up to produce a set of 1:M
relationships
– Can avoid problems inherent to M:N relationship by creating a
composite entity or bridge entity
• This will be used to link the tables that were originally related
in a M:N relationship
• The composite entity structure includes-as foreign keys-at
least the primary keys of the tables that are to be linked.
The M:N Relationship Between STUDENT and CLASS
This CANNOT be implemented as shown next…..
Bowser
Smithson
Accounting 1 (ACCT-211)
Intro to Microcomputing (CIS-220)
Intro to Statistics (QM-261)
The tables have many redundancies!!
+ CLASS_CODE
CLASS_CODE
+ STU_NUM
Changing the M:N relationship to TWO 1:M relationships
Converting the M:N relationship into TWO 1:M relationships
Foreign keys reference the primary keys in the other tables of which it has a relationship with
The database designer has 2 main options to define a composite table’s primary key: either
use the combination of those foreign keys or create a new primary key.
Mandatory vs. Optional Cardinalities
• Specifies whether an instance must exist or can be absent in the relationship
Lecturer Classhandles
A Lecturer may handle zero or many classes.
A class is handled by one and only one Lecturer.
OptionalOptionalMandatoryMandatory
(0,N)(1,1)
Lecturer Class
(0,N) (1,1)
handles1 M
42
Weak Entities
• Weak entity meets two conditions
– Existence-dependent• Cannot exist without entity with which it has a
relationship
– Has primary key that is partially or totally derived from parent entity in relationship
• Database designer usually determines whether an entity can be described as weak based on business rules
ERD :: 19 / 1 / 07 43
43
Weak Entities (continued)
44
Recursive Relationships
• Relationship type where same entity type participates more than once in different roles
• Relationship can exist between occurrences of the same entity set
• Naturally found within unary relationship
Recursive Relationships
45
ERD :: 19 / 1 / 07 46
46
Recursive Relationships (continued)
ERD :: 19 / 1 / 07 47
47
Recursive Relationships (continued)
How to Evaluate a Data Model?
• A good data model has the following:– Accuracy and completeness
– Non redundancy
– Enforcement of business rules
– Data Reusability
– Stability and Flexibility
– Communication Effectiveness
– Simplicity
Lesson Summary
• ERD is a diagram that can be used to represent structure of a database.
• There are 3 main components of a database structure (1) entity (2) attribute (3) relationship
• All entities must be directly connected to at least one other entity in the ERD.
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