This document provides an overview of basic database analysis concepts including: - Business rules that define entities, attributes, and relationships. - Entity-relationship (ER) modeling which involves defining entities, attributes, relationships, and cardinalities between entities. - Different types of entities (strong, weak), attributes (simple, composite, multivalued), and relationships (unary, binary, ternary). - Key concepts like identifiers, degrees of relationships, and modeling time-dependent data with time stamps.

1. Lecture 3:
Basic Database Analysis
ISOM3260, Spring 2014

2. 2
Where we are now
• Database environment
– introduction to database
• Database development process
– steps to develop a database
• Conceptual data modeling
– entity-relationship (ER) diagram; enhanced ER
• Logical database design
– transforming ER diagram into relations; normalization
• Physical database design
– technical specifications of the database
• Database implementation
– Structured Query Language (SQL), Advanced SQL
• Advanced topics
– data and database administration

3. 3
Database development activities during SDLC
Top-down
analysis

4. 4
Basic Database Analysis
• Business Rules
• E-R Model
• Entities
• Attributes
• Relationships

5. 5
Business Rules
• Statements that define or constrain some aspect of the
business
• Include
– names and definitions of entity types, attributes, and
relationships
– constraints on above data objects
• Expressed in terms familiar to end users
– e.g. Every student in the university must have a faculty
advisor
• Automated through DBMS software
• Some business rules cannot be represented in E-R
diagram; instead they are stated in natural language

6. 6
Figure 2-1: Sample E-R Diagram

7. 7
Figure 2-2: Basic E-R Notation
Entity
symbols
Relationship
symbols
Attribute
symbols
A special
entity that is
also a
relationship

8. 8
E-R Model Constructs
• Entity - person, place, object, event, concept
• Entity Type versus Entity Instance

9. 9
What Should an Entity Be?
• SHOULD BE:
– 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
• SHOULD NOT BE:
– a user of the database system
– an output of the database system (e.g. a report)

10. 10
Inappropriate entities
System user System output
Appropriate entities
Figure 2-4

11. 11
Strong vs. Weak Entity Type
• Strong entity
– exists independently of other types of entities
– has its own unique identifier
– represented with single-line rectangle
• Weak entity
– dependent on a strong entity…cannot exist on its own
– does not have a unique identifier
– represented with double-line rectangle
• Identifying relationship
– links strong entities to weak entities
– represented with double line diamond

12. 12
Figure 2-5: Strong and weak entities

13. 13
Attributes
• Attribute
– property or characteristic of an entity type
• Classifications of attributes
– Simple versus Composite Attribute
– Single-Valued versus Multivalued Attribute
– Stored versus Derived Attributes
– Identifier Attributes

14. 14
Figure 2-7: A composite attribute
An attribute
broken into
component parts

15. 15
Figure 2-8: Entity with a multivalued attribute (Skill) and
derived attribute (Years_Employed)
Derived
from date employed and current date
Multivalued:
an employee can have
more than one skill

16. 16
Identifier Attribute
• Identifier (or key)
– an attribute (or combination of attributes) that
uniquely identifies individual instances of an entity
type
• Simple Key versus Composite Key
• Candidate Key
– an attribute that could be a key…satisfies the
requirements for being a key

17. 17
Characteristics of Identifiers
• Will not change in value
• Will not be null
• No intelligent identifiers
– e.g. containing locations that might change
• Substitute new, simple keys for long, composite keys
– e.g. Game_Number instead of Home_Team and
Visiting_Team

18. 18
Figure 2-9a: Simple key attribute
The key is underlined

19. 19
Figure 2-9b: Composite key attribute
The key is composed
of two subparts

20. 20
Relationships
• Relationship Types vs. Relationship Instances
– the relationship type is modeled as the diamond
and lines between entity types…the instance is
between specific entity instances
• Relationships can have attributes
– these describe features pertaining to the
association between the entities in the relationship

21. 21
Figure 2-10a: Relationship type (Completes)
Figure 2-10b: Relationship instances

22. 22
Figure 2-11a: A binary relationship with an attribute
Here, the Date_Completed attribute refers to the employee’s
completion of a course…it is an attribute of the relationship

23. 23
Associative Entities
• It’s an entity – it has attributes
• AND it’s a relationship – it links entities together
• When should a relationship with attributes instead be an
associative entity?
– all relationships for the associative entity should be many
– the associative entity could have meaning independent of the other
entities
– the associative entity preferably has a unique identifier, and should
also have other attributes
– the associative entity may be participating in other relationships other
than the entities of the associated relationship
– ternary relationships should be converted to associative entities

24. 24
Figure 2-11b: An associative entity (CERTIFICATE)
Associative entity involves a rectangle with a diamond inside.
Note that the many-to-many cardinality symbols face toward
the associative entity and not toward the other entities.

25. 25
Degree of a Relationship
• Degree of a Relationship is the number
of entity types that participate in it
– Unary Relationship (degree 1)
– Binary Relationship (degree 2)
– Ternary Relationship (degree 3)

26. 26
Figure 2-2: Degree of relationships
One entity
related to
another of
the same
entity type
Entities of
two different
types related
to each other
Entities of three
different types
related to each
other

27. 27
Figure 2-12a: Unary relationships

28. 28
Representing a bill-of -materials structure
Figure 2-13a: A unary relationship with an attribute. This
has a many-to-many relationship

29. 29
(b) Two instances

30. 30
Figure 2-13c: An associative entity – bill of materials structure

31. 31
Figure 2-12b: Binary relationships

32. 32
Figure 2-12c: Ternary relationships

33. 33
Figure 2-14: Ternary relationships as an associative entity

34. 34
Cardinality of Relationships
• One–to–One
– each entity instance in the relationship will have
exactly one related entity instance
• One–to–Many
– an entity instance on one side of the relationship can
have many related entity instances, but an entity
instance on the other side will have a maximum of
one related entity instance
• Many–to–Many
– entity instances on both sides of the relationship can
have many related entity instances on the other side

35. 35
Cardinality Constraints
• Cardinality Constraints
– the number of instances of one entity that can or must
be associated with each instance of another entity
• Minimum Cardinality
– if zero, then optional
– if one or more, then mandatory
• Maximum Cardinality
– the maximum number

36. 36
Figure 2-2: Cardinality

37. 37
Figure 2-16a: Basic relationship with only maximum cardinalities
showing
Figure 2-17a: Mandatory cardinalities

38. 38
Figure 2-17b: One optional, one mandatory cardinality

39. 39
Figure 2-17c: Optional cardinalities

40. 40
Figure 2-18: Cardinality constraints in a ternary relationship

41. 41
More about Relationships
• Modeling Time-Dependent Data
– Time Stamps (such as date and time)
• Multiple Relationships
– more than one relationship between the same
entity types

42. 42
Figure 2-19: Example of time stamping

43. 43
Examples of multiple relationships – entities can be related to
one another in more than one way
Figure 2-21a: Employees and departments

44. 44
Figure 2-21b: Professors and courses (fixed upon constraint)
Maximum
cardinality
constraint is 4

45. 45
Figure 2-22: E-R diagram for Pine Valley Furniture