SI 654
Database Application Design
Winter 2003
Dragomir R. Radev
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© 2002 by Prentice Hall
Database Processing
Eighth Edition
The EntityRelationship
Model
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Chapter 3
David M. Kroenke
© 2002 by Prentice Hall
Data Modeling
• Process of creating a logical
representation of the structure of
the database
• The most important task in database
development
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Entity-Relationship Model
(E-R Model)
• An Entity-Relationship Model (E-R
Model) consists of:
– Entities
– Attributes
– Identifiers
– Relationships
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An Entity
• An entity is an object that can be
identified in the users’ work
environment & that users want to
track.
• Entities of a given type are grouped
into entity classes.
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An Entity Example
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Attributes
• An attribute describes a characteristic of
an entity
• For example
– An entity: Employee
– Has attributes:
• EmployeeName
• Extension
• DateOfHire
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Identifier
• An identifier uniquely identifies a row
in a table.
• For an Employee, the
SocialSecurityNumber may serve as
the Indentifier.
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Relationships
• A relationship describes how one or
more entities are related with each
other.
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Relationship Cardinality
• Entity-Instance Participation in
relationships is shown by
– maximum cardinality
– minimum cardinality
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Maximum Cardinality
• The maximum cardinality
indicates/depicts the maximum
number of instances involved in a
relationship.
• Alternatives include
– 1:1 (one-to-one)
– 1:N (one-to-many)
– N:M (many-to-many)
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Relationship Examples
Showing Maximum
Cardinality Alternatives
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Minimum Cardinality
• The minimum cardinality
indicates/depicts whether
participation in the relationship is
mandatory or optional.
• Alternatives include
– 0 (optional)
– 1 (mandatory)
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A Relationship Example
Showing Minimum and
Maximum Cardinality
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A Recursive Relationship
• A recursive
relationship is when
an entity has a
relationship with
itself.
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Entity-Relationship Diagram
(E-R Diagram)
• An entity-relationship diagram (E-R
Diagram) is a graphical representation
of the E-R model using a set of
‘somewhat’ standardized conventions
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An Entity-Relationship Diagram
(E-R Diagram) Example
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Weak Entity
• A weak entity is an entity whose
instance survival depends (logically)
on an associated instance in another
entity
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Subtype Entities
• Some entities may have many common
attributes and a few unique
attributes.
• The common attributes may be
grouped together in a supertype
entity and the unique attributes may
be grouped together in a subtype
entity.
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CLIENT with
Subtype Entities
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E-R Diagram
Computer Assisted Software
Engineering (CASE) Tools
• Several Computer Assisted Software
Engineering (CASE) Tools exist to help
create E-R Diagrams and the resulting
physical database elements. Products
include:
– IEW
– IEF
– DEFT
– ER-WIN
– Visio
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E-R Diagram Example:
Jefferson Dance Club
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E-R Diagram Example:
San Juan Charters
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Database Processing
Eighth Edition
The
Relational
Model and
Normalization
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Chapter 5
David M. Kroenke
© 2002 by Prentice Hall
The Relational Model
• Broad, flexible model
• Basis for almost all DBMS products
• E.F. Codd defined well-structured
“normal forms” of relations,
“normalization”
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Components of the
Relational Model
• Relation
– A two-dimensional table consisting
of rows and columns
• Tuples
– The rows (or records) in a relation
• Attributes
– The columns (or fields) in a relation
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Terminology
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Functional Dependency
• Functional dependencies are the
relationships among the attributes
within a relation.
• If attribute A functional depends on
attribute B, then for every instance
of B you will know the respective
value of A.
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Functional Dependency
Notation
• Major is functionally dependent on
SID
• SID  Major
• Grade is functionally dependent on
the combination of SID and ClassID
• (SID, ClassID)  Grade
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Functional Dependency
– an Example
• EmployeeNumber  Name
• EmployeeNumber  Age
• EmployeeNumber  Sex
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A Key
• A key is a group of
one or more
attributes that
uniquely identifies
a tuple
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A Combination Key
• Sometimes more than one attribute
will be required to uniquely identify a
tuple.
• If a key consists of more than one
attribute, it is called a combination
(or composite) key.
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Example of a Combination
Key
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Normalization
• Normalization is a process of
evaluating and converting a relation to
reduce modification anomalies
• Essentially, normalization detects and
eliminates data redundancy
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An Anomaly
• An anomaly is an undesirable
consequence of a data modification.
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Normal Forms
• Normal forms are state-classes of
relations which identify the level of
anomaly-avoidance
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Normal Forms Levels
•
•
•
•
•
•
•
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1NF –First Normal Form
2NF –Second Normal Form
3NF –Third Normal Form
BCNF –Boyce-Codd Normal Form
4NF –Fourth Normal Form
5NF –Fifth Normal Form
DK/NF –Domain/Key Normal Form
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First Normal Form (1NF)
• To be in First Normal Form (1NF) a
relation must have only single-valued
attributes -- neither repeating groups
nor arrays are permitted
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Second Normal Form (2NF)
• To be in Second Normal Form (2NF)
the relation must be in 1NF and each
nonkey attribute must be dependent
on the whole key (not a subset of the
key)
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Third Normal Form (3NF)
• To be in Third Normal Form (3NF) the
relation must be in 2NF and no transitive
dependencies may exist within the relation.
• A transitive dependency is when an
attribute is indirectly functionally
dependent on the key (that is, the
dependency is through another nonkey
attribute)
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Violation of 3NF
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Boyce-Codd Normal Form
(BCNF)
• To be in Boyce-Codd Normal Form
(BCNF) the relation must be in 3NF
and every determinant must be a
candidate key.
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Fourth Normal Form (4NF)
• To be in Fourth Normal Form (4NF)
the relation must be in BCNF and the
relation may not contain multi-valued
dependencies.
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Fifth Normal Form (5NF)
• The Fifth Normal Form concerns
dependencies that are obscure and
beyond the scope of this text.
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Domain/Key Normal Form
(DK/NF)
• To be in Domain/Key Normal Form
(DK/NF) every constraint on the
relation must be a logical consequence
of the definition of keys and domains.
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DK/NF Terminology
• Constraint
– A rule governing static values of
attributes
• Key
– A unique identifier of a tuple
• Domain
– A description of an attribute’s
allowable values
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 DK/NF Example
Domain/Key
Definition
of Example
Above 
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DK/NF Example
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DK/NF Example
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Summary of Normal Forms
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Synthesis of Relations
A  B and B  A
A  B but B not  A
A not  B and B not  A
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one-to-one
many-to-one
many-to-many
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Summary of Attribute
Relationships
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Optimization
• De-Normalization (a.k.a., Controlled
Redundancy)
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