Chapter Three
( Relational Data Model)
Objectives
Introduction to Relational Data Models.
 Advantages of Relational Data Models.
 Restriction of Relational Data Model.
 Keys.
 What are a good BD Design?

Relational Data Model:
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Developed by Codd in 1970.
Conceptually simple.
Based on mathematical set theory.
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Relational Data Model:

Most important advantage of the
RDBMS is its ability to hide the
complexities of the relational model
from the user.
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Relational Database Models:
Data are represented as a set of
tables.

Structure

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A set of tables ( Relations).
Each relation has a unique name.
Each relation has a set of attributes.
Each relation has a set of tuples.
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Restriction on Relational DBMS
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No two tuples are the same.
No two attributes are the same.
Order of tuples are immaterial.
Order of attributes are immaterial.
Value of attributes must be atomic.
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Relational Database Example:
Students
Courses
Faculty
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Attributes of a Relation:
Students (Name, ID, Major, Minor,….)
Courses (C_num, Dept, Cr, Description)
Faculty (Name, ID, SSN, …..)
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Tuples:
Students
(Name, ID, Major, Minor,….)
_________________________________
John Smith 1111, ITEC, VART
Mary Smith 2222, COSC, ITEC
Lorry Joys 4444, ACCT, COSC
Courses
(C_num, Dept, Cr, Description)
_______________________________________
345
ITEC
3 Databases I
445
ITEC
3 Databases II
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Keys:
(Constraints)
A set of attributes whose values uniquely
identify each entity.
Examples:
Students (Name, ID, Major, Minor,….)
Courses (C_num, Dept, Cr, Description)
Faculty (Name, ID, SSN, …..)
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Keys:
(Constraints)
Primary key:
1- Uniqueness:
At any given time, no two tuples can have the
same value for a given primary key.
2-Minimally:
None of the attributes in primary key can be
discarded without distorting the uniqueness
property
3-Selection:
A key selected by the Database Administrator.
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Primary key:
Key’s role is based on determination


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If you know the value of attribute A, you
can look up (determine) the value of
attribute B.
ID  GPA
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Keys

Composite key

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Key attribute

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Any attribute that is part of a key.
Superkey

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Composed of more than one attribute.
Any combination of attributes that uniquely
identifies each row.
Candidate key
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Keys:
(Constraints)
Foreign key:
An attribute(s) in an entity set (relation)
which is the primary key of other entity
set (relation)

Example:
Department(Name, Dept_Id, ….)
Faculty(Name, Id, Dept_Id,…)
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Normal Forms
(Guidelines for RD design)
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How do we know this is a good design?
If it is not a good design, What should
we do?
Modify our design ??.
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Normalization:

Process for evaluating and correcting table
structures to minimize data redundancies

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Reduces data anomalies
Works through a series of stages called
normal forms:
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First normal form (1NF)
Second normal form (2NF)
Third normal form (3NF)
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Why Normalize Tables:
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Structure of data does not handle data
very well
The table structure appears to work;
Report generated with ease
Unfortunately, report may yield
different results depending on what
data anomaly has occurred
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
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Each table represents a single subject
No data item will be unnecessarily
stored in more than one table
All attributes in a table are dependent
on the primary key
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Normal Forms
(Guidelines for RD design)

A relation is in 1NF if the values of
domain is atomic for each attribute.
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First Normal Form: 1NF
Example:
 Person (Name
Smith

Person (Name
Smith
Smith
Smith
Age Children )
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John, Lori, Mark
Age Children )
42
42
42
John
Lori
Mark
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First Normal Form: 1NF
Example:
 Student (


Name
Birthday
S1
S2
Feb 2,91
March 8,88
)
Student (Name, D_Birth, M_Birth, Y_Birth)
Note: 2NF and 3NF Deal with the relationship
between non-key and key
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First Normal Form:

Repeating group
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Derives its name from the fact that a group
of multiple entries of same type can exist
for any single key attribute occurrence
Relational table must not contain
repeating groups
Normalizing table structure will reduce
data redundancies
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Second Normal Form: 2NF

A relation is in 2NF if it is in 1NF and
every attribute is Fully dependent on
the entire key in this relation.
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Second Normal Form: 2NF
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Example: R(A,B,C,D)
A, B ---> C, D
A ---> D

D partially depends on A,B
C fully depends on A,B
A&B are prime (part of key)
If A is primary key. Is this in 2NF?
If A&B is primary key. Is this in 2NF?
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Second Normal Form: 2NF

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What should we do with a relation which is
not in 2NF?
Example: R(A,B,C,D)

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A, B ---> C, D
A ---> D
R1 (A,B,C)
R2(A,D)
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Second Normal Form: 2NF

Example:
R(Part Warehouse
P1
W1
P2
W1
P3
P4
P4
W2
W4
W1
Address
Frostburg
Frostburg
Quantity
25
30
Cumberland 32
Frostburg
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What is the primary key?
Part, Warehouse ---> Quantity
Warehouse ---> Address
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Second Normal Form: 2NF

Problems:
1.
Repetition of information:
Changing the address W!
2.
Unable to present information:
Warehouse with no part

So …
R1 (Warehouse, Address)
R2 (Part, Warehouse, Quantity)
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Second Normal Form: 2NF

R(
Example:
Professor, Student, Course, Degree
P1
P2
P3
S1
S2
S2
C1
C2
C4
Ph.D.
M.S.
M.S.
P4
S3
C4
Ph.D.
Professor ---> Course
Student ---> Degree
Professor ---> Student
)
Key? Not in 2NF
R1(Student, Degree)
R2(Professor, Course, Student)
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Third Normal Form (3NF):
 A relation is 3NF if it is in 2NF and every
non-key attribute non transitively depends
on the Primary Key.

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Example: R(A,B,C,D)
A, B --->D
D ---> C
R1(A,B,D)
R2(D,C)

Fact: 3NF is violated when a non-key is a
fact about another non-key

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Third Normal Form (3NF):

Example: R(Employee, Dept, Location)
Employee ---> Dept
Dept ---> Location

Employee
Dept
Location
E1
E2
E3
D1
D2
D3
Frostburg
Frostburg
Frostburg
Problems?
R1(Employee, Dept)
R2(Dept, Location)
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Third Normal Form (3NF):
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Example: R(A,B,C,D)
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A,B ---> C
A,C ---> D
So A,B is the Primary Key
Not in 3NF
R1(A,B,C)
R2(A,C,D)
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Null Values:
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No data entry
Not permitted in primary key
It is represent as:
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An unknown attribute value
A known, but missing, attribute value
A “not applicable” condition
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Controlled redundancy:
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Makes the relational database work
Tables within the database share common
attributes that enable the tables to be
linked together
Multiple occurrences of values in a table
are not redundant when they are required
to make the relationship work
Redundancy exists only when there is
unnecessary duplication of attribute values
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