The document provides information about entity relationship diagrams (ERDs) and data modeling. It discusses the objectives of data modeling which include understanding relationships between entities and incorporating them into database design. It also explains how to identify entities, attributes, and relationships based on nouns, descriptors, and verbs connecting entities. The document outlines the key components of ERDs including entities, attributes, relationships, cardinalities, and identifiers. It provides examples of a data model for a restaurant and explains how ERDs can be used as an effective communication and documentation tool.

1. ER Modeling

2. Part # 2
2
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

3. Part # 2
Data Model
 Model: an abstraction of a real-world object
or event
 Useful in understanding complexities of the real-
world environment
 Data model
 A diagram that displays a set of tables and the
relationships between them
 Next Slide: “Restaurant” Access data model
using Entity Relationship Diagram (ERD)

4. Part # 2
Access Data Model using ERD
4

5. Part # 2
What is an Entity Relationship
Diagram (ERD)?
 ERD is a data modeling technique used in
software engineering to produce a conceptual
data model of an information system.
 So, ERDs illustrate the logical structure of
databases.
 ERD development using a CASE tool
 Powerdesigner by SAP
 Data Modeler by Orcale
5

6. Part # 2
The Importance of Data Model
 Blue print: official documentation
 Blue print of house
 Employee’s w/o DB knowledge can understand
 a data model diagram vs. a list of tables
 Used as an effective Communication Tool
 Improve interaction among the managers, the
designers, and the end users
 Independence from a particular DBMS
 Network DB, Object-oriented DB, etc.

7. Part # 2
7
 The data modeling revolves around discovering
and analyzing organizational and users data
requirements.
 Requirements based on policies, meetings,
procedures, system specifications, etc.
 Identify what data is important
 Identify what data should be maintained
Data Model (con’t)

8. Part # 2
8
 The major activity of this phase is identifying
entities, attributes, and their relationships to
construct model using the Entity Relationship
Diagram.
 Entity  table
 Attribute  column
 Relationship  line
 Basics of Data Modeling Video
 Until business rules # 3 (9:20)
ERD

9. Part # 2
9
How to find entities?
 Entity:
 "...anything (people, places, objects, events, etc.)
about which we store information (e.g. supplier,
machine tool, employee, utility pole, airline seat,
etc.).”
 Tangible: customer, product
 Intangible: order, accounting receivable
 Look for singular nouns (beginner)
 BUT a proper noun is not a good candidate….

10. Part # 2
10
Entity Instance
Entity 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

11. Part # 2
11
How to find attributes?
 Attribute:
 Attributes are data objects that either identify or
describe entities (property of an entity).
 In other words, it is a descriptor whose values are
associated with individual entities of a specific entity
type
 The process for identifying attributes is similar except now
you want to look for and extract those names that appear
to be descriptive noun phrases.

12. Part # 2
12
How to find relationships?
 Relationship:
 Relationships are associations between entities.
 Typically, a relationship is indicated by a verb
connecting two or more entities.
 Employees are assigned to projects
 Relationships should be classified in terms of
cardinality.
 One-to-one, one-to-many, etc.

13. Part # 2
13
How to find cardinalities?
 Cardinality:
 The cardinality is the number of occurrences in one
entity which are associated to the number of
occurrences in another.
 There are three basic cardinalities (degrees of
relationship).
 one-to-one (1:1), one-to-many (1:M), and many-to-
many (M:N)

14. Part # 2
14
“attributes that uniquely identify entity instances”
 Becomes a PK in RDS
 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)
Identifier

15. Part # 2
Crow’s Foot Notation
 Known as IE notation (most popular)
 Entity:
 Represented by a rectangle, with its name on the
top. The name is singular (entity) rather than
plural (entities).
15

16. Part # 2
Attributes
 Identifiers are represented by underlying the
name of the attribute(s)
16

17. Part # 2
Basic Cardinality Type
 1-to-1 relationship
 1-to-M relationship
 M-to-N relationship

18. Part # 2
Cardinality con’t

19. Part # 2
19
Example Model

20. Part # 2
Data Model by Peter Chen’ Notation
(first - original)

21. Part # 2
Business Rule Example 1
 Finalized business rules must be
bi-directional.
 Draft: one sentence
 Finalized: two sentences
 A professor advises many
students (professor to student).
Each student is advised by one
professor (student to professor).
 A professor must teach many
classes. Each class must be
taught by one professor.
21

22. Part # 2
Business Rule 1
 Business Rules are used to define entities, attributes,
relationships and constraints.
 Usually though they are used for the organization
that stores or uses data to be an explanation of a
policy, procedure, or principle.
 The data can be considered significant only after
business rules are defined.
 W/o them it cannot be considered as data for RDS but just
records.
22

23. Part # 2
Business Rule 2
 When creating business rules, keep them simple,
easy to understand, and keep them broad.
 so that everyone can have a similar understanding and
interpretation.
 Sources of business rules:
 Direct interviews with internal & external stakeholders
 Site visitations (collect data) and observation of the work
process or procedure
 Review and study of documents (Policies, Procedures,
Forms, Operation manuals, etc..)
23

24. Part # 2
Discovering Business Rules
 Real world example on the class website
 After reviewing and studying the interview and
various forms, develop a draft business rules -
does not need to be bi-directional and less precise
wording…
 Keep on going until “optimized”
 Then, finalize Business Rules: bi-directional.

25. Part # 2
Business Rule Example 2
 A sales representative must write
many invoices. Each invoice has to
be written by one sales
representative.
 Each sales representative must be
assigned to many department.
Each department has only one
sales representative.
 A customer has to generate many
invoices. An invoice is generated
by only one customer.
25

26. Part # 2
26
“Describe detail information about an entity ”
 Entity: Employee
 Attributes:
 Employee-Name
 Address (composite)
 Phone Extension
 Date-Of-Hire
 Job-Skill-Code
 Salary
Attributes

27. Part # 2
27
Classes of attributes
 Simple attribute
 Composite attribute
 Derived attributes
 Single-valued attribute
 Multi-valued attribute

28. Part # 2
28
 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 attribute

29. Part # 2
29
 is not physically stored within the database
 instead, it is derived by using an algorithm.
 Example 1: Late Charge of 2%
 MS Access: InvoiceAmt * 0.02
 Example 2: AGE can be derived from the date of
birth and the current date.
 MS Access: int(Date() – Emp_Dob)/365)
Derived attribute

30. Part # 2
30
 can have only a single (atomic) value.
 Examples:
 A person can have only one social security number.
 A manufactured part can have only one serial number.
 A single-valued attribute is not necessarily a
simple attribute.
 Part No: CA-08-02-189935
 Location: CA, Factory#:08, shift#: 02, part#: 189935
Single-valued attribute

31. Part # 2
31
 can have many values.
 Examples:
 A person may have several college degrees.
 A household may have several phones with
different numbers
 A car color
Multi-valued attributes

32. Part # 2
32
Example - “Movie Database”
 Entity:
 Movie Star
 Attributes:
 SS#: “123-45-6789” (single-valued)
 Cell Phone: “(661)123-4567, (661)234-5678”
(multi-valued)
 Name: “Harrison Ford” (composite)
 Address: “123 Main Str., LA, CA” (composite)
 Gender: “Female” (simple)
 Age: 24 (derived)

33. Part # 2
Procedure of ERD
 Relatively simple representations of complex
real-world data structures
 Data modeling is iterative process.
 “complete” and “100% error free” model is
not possible!
 Only “Optimized” model is possible….
33

34. Part # 2
ER Model Basics
 Entity: Real-world object distinguishable from
other objects. An entity is described (in DB)
using a set of attributes.
 Entity Set: A collection of similar entities. E.g.,
all employees.
 All entities in an entity set have the same set of
attributes. (Until we consider ISA hierarchies,
anyway!)
 Each entity set has a key.
 Each attribute has a domain.
Employees
ssn
name
lot

35. Part # 2
ER Model Basics (Contd.)
 Relationship: Association among two or more entities. E.g.,
Attishoo works in Pharmacy department.
 Relationship Set: Collection of similar relationships.
 An n-ary relationship set R relates n entity sets E1 ... En; each
relationship in R involves entities e1 E1, ..., en En
 Same entity set could participate in different relationship sets, or
in different “roles” in same set.
lot
dname
budget
did
since
name
Works_In Departments
Employees
ssn
Reports_To
lot
name
Employees
subor-
dinate
super-
visor
ssn

36. Part # 2
Participation Constraints
 Does every department have a manager?
 If so, this is a participation constraint: the participation of
Departments in Manages is said to be total (vs. partial).
 Every did value in Departments table must appear in a
row of the Manages table (with a non-null ssn value!)
lot
name dname
budget
did
since
name dname
budget
did
since
Manages
since
Departments
Employees
ssn
Works_In
0,M 1,M
1,1 1,M

37. Part # 2
Structural Constraints
 Participation
 Do all entity instances participate in at least
one relationship instance?
 Cardinality
 How many relationship instances can an
entity instance participate in?
(min,max) (min,max)
Participation Cardinality
0 -- Partial 1 -- one
1 -- Total (Mandatory) M -- more than one

38. Part # 2
Weak Entities
 A weak entity can be identified uniquely only by
considering the primary key of another (owner) entity.
 Owner entity set and weak entity set must participate in a
one-to-many relationship set (one owner, many weak
entities).
 Weak entity set must have total participation in this
identifying relationship set.
lot
name
age
pname
Dependents
Employees
ssn
Policy
cost

39. Part # 2
ISA (`is a’) Hierarchies
Contract_Emps
name
ssn
Employees
lot
hourly_wages
Hourly_Emps
contractid
hours_worked
As in C++, or other
PLs, attributes are
inherited.
If we declare A ISA
B, every A entity is
also considered to be a
B entity.
 Overlap constraints: Can Joe be an Hourly_Emps as well as a
Contract_Emps entity? (Allowed/disallowed)
 Covering constraints: Does every Employees entity also have
to be an Hourly_Emps or a Contract_Emps entity? (Yes/no)
 Reasons for using ISA:
 To add descriptive attributes specific to a subclass.
 To identify entitities that participate in a relationship.

40. Part # 2
Conceptual Design Using the ER
Model
 Design choices:
 Should a concept be modeled as an entity or an attribute?
 Should a concept be modeled as an entity or a relationship?
 Identifying relationships: Binary or ternary? Aggregation?
 Constraints in the ER Model:
 A lot of data semantics can (and should) be captured.
 But some constraints cannot be captured in ER diagrams.

41. Part # 2
Entity vs. Attribute
 Should address be an attribute of Employees or an
entity (connected to Employees by a relationship)?
 Depends upon the use we want to make of address
information, and the semantics of the data:
 If we have several addresses per employee,
address must be an entity (since attributes cannot
be set-valued).
 If the structure (city, street, etc.) is important,
e.g., we want to retrieve employees in a given
city, address must be modeled as an entity (since
attribute values are atomic).

42. Part # 2
Converting model to design
 Many-to-many relationships
 Each entity becomes a table
 The relationship becomes a table
 PKs of entities becomes FKs in the
relationship
 Student( )
 Course( )
 Takes( )
takes
Student Course
StudentID
Name
Class
Major
Courseno
Coursename
Credits
semester
0:M 0:M

43. Part # 2
Model to design (contd.)
 1-Many relationships
 Entities become tables
 Copy PK of multi-participant to single
participant
 Copy attributes of relationship to single
participant (why?)
includes
Computer Part
ComputerID
Make
Model
Year
Partno
Type
Make
installdate
1:M 0:1

44. Part # 2
Model to design (contd.)
 1-1 relationships
 Entities can be merged, or
 copy PK of any entity to the other
 Generalization
 Copy PK of parent entity to child entity
 Weak entities
 Copy PK of controlling entity to weak entity