3/1/2007 IFS310: Module 6 Data Modeling and Entity-Relationship Diagrams
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3/1/2007
IFS310: Module 6
Data Modeling and Entity-Relationship
Diagrams
3/1/2007
IFS310: Module 6
Systems Modeling
• A model is a representation of reality. Just as a picture is worth a thousand words, most system models are pictorial representations of reality.
• Data modeling is a technique for organizing and documenting a system’s DATA. Data modeling is sometimes called database modeling because a data model is usually implemented as a database.
3/1/2007
IFS310: Module 6
3/1/2007
IFS310: Module 6
System Concepts
Systems thinking is the application of formal systems theory and concepts to systems problem solving.
An ERD depicts data in terms of the entities and relationships described by the data.
3/1/2007
IFS310: Module 6
Entities
An entity is something about which we want to store data.
An entity is a class of persons, places, objects, events, or concepts about which we need to capture and store data.
An entity instance is a single occurrence of an entity.
3/1/2007
IFS310: Module 6
Attributes
• An attribute is a descriptive property or characteristic of an entity. Synonyms include element, property, and field
3/1/2007
IFS310: Module 6
Attributes - Identification
Every entity must have an identifier or key.– An key is an attribute, or a group of attributes,
which assumes a unique value for each entity instance. It is sometimes called an identifier.
Sometimes more than one attribute is required to uniquely identify an instance of an entity.– A group of attributes that uniquely identifies an
instance of an entity is called a concatenated key. Synonyms include composite key and compound key.
3/1/2007
IFS310: Module 6
Relationships
A relationship is a natural business association that exists between one or more entities. The relationship may represent an event that links the entities, or merely a logical affinity that exists between the entities.
A connecting line between two entities on an ERD represents a relationship.
A verb phrase describes the relationship.– All relationships are implicitly bidirectional, meaning
that they can interpreted in both directions.
3/1/2007
IFS310: Module 6
3/1/2007
IFS310: Module 6
Cardinality
Each relationship on an ERD also depicts the complexity or degree of each relationship, and this is called cardinality.– Cardinality defines the minimum and maximum
number of occurrences of one entity for a single occurrence of the related entity. Because all relationships are bi-directional, cardinality must be defined in both directions for every relationship.
3/1/2007
IFS310: Module 6
C a r d i n a l i t yI n t e r p r e t a t i o n
M i n i m u mI n s t a n c e s
M a x i m u mI n s t a n c e s
G r a p h i c N o t a t i o n
E x a c t l y o n e 1 1
Z e r o o r o n e 0 1
O n e o r m o r e 1 m a n y ( > 1 )
Z e r o , o n e , o r m o r e 0 m a n y ( > 1 )
M o r e t h a n o n e > 1 > 1
F i g u r e 5 . 3
3/1/2007
IFS310: Module 6
Foreign Keys
A relationship implies that instances of one entity are related to instances of another entity.
To be able to identify those instances for any given entity, the primary key of one entity must be migrated into the other entity as a foreign key.– A foreign key is a primary key of one entity that is contributed
to (duplicated in) another entity for the purpose of identifying instances of a relationship. A foreign key (always in a child entity) always matches the primary key (in a parent entity).
3/1/2007
IFS310: Module 6
3/1/2007
IFS310: Module 6
(a)
(b)
3/1/2007
IFS310: Module 6
Data Modeling During Systems Analysis
1 A key-based data model will be drawn first. 2 A fully attributed data model will be
constructed along with the process of analysis and design.
– Each attribute is defined in the repository with data types, domains, and defaults.
3/1/2007
IFS310: Module 6
How to Construct Data Models
1st Step - Entity Discovery The first task is to discover those fundamental entities in the
system. There are several techniques that may be used to identify entities.
During interviews or JAD sessions with system owners and users, pay attention to key words in their discussion.
During interviews or JAD sessions, specifically ask the system owners and users to identify things about which they would like to capture, store, and produce information.
Study existing forms and files. Some CASE tools can reverse engineer existing files and
databases into physical data models.
3/1/2007
IFS310: Module 6
How to Construct Data Models
1st Step - Entity Discovery An entity has multiple instances Entities should be named with nouns that describe the person,
event, place, or intangible thing about which we want to store data. Define each entity in business terms.
3/1/2007
IFS310: Module 6
How to Construct Data Models
2nd Step - The Context Data Model The second task in data modeling is to construct the context data
model. The context data model includes the fundamental or independent entities that were previously discovered.
• An independent entity is one which exists regardless of the existence of any other entity. Its primary key contain no attributes that would make it dependent on the existence of another entity.
• Independent entities are almost always the first entities discovered in your conversations with the users.
Relationships should be named with verb phrases that, when combined with the entity names, form simple business sentences or assertions.
• If only one-way naming is used, always name the relationship from parent-to-child.
3/1/2007
IFS310: Module 6
3/1/2007
IFS310: Module 6
How to Construct Data Models
3rd Step - The Key-Based Data Model The third task is to identify the keys of each entity. If you cannot define keys for an entity, it may be that the entity
doesn’t really exist—that is, multiple occurrences of the so-called entity do not exist.
3/1/2007
IFS310: Module 6
3/1/2007
IFS310: Module 6
How to Construct Data Models
4th Step - Generalized Hierarchies At this time, it would be useful to identify any generalization
hierarchies in a business problem.
5th Step - The Fully Attributed Data Model The fifth task is to identify the remaining data attributes.
6th Step - The Fully Described Model The last task is to fully describe the data model. Most CASE tools provide extensive facilities for describing the
data types, domains, and defaults for all attributes to the repository.
3/1/2007
IFS310: Module 6
Group Project
• Objectives– Milestone 2 (Data Model)
– Milestone 3• Overviews• Domain of Changes• Narrative descriptions of processes (data flows,
data stores, external entities)• DFDs and ER diagrams
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