An Introduction to Data Modelling
Entity Relationship Modelling
Avin Mathew
amathew@smsmt.com
Nov 2010
WHY do we model data?
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WHAT is a data model?
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An album has an a creating artist, a title, recommended price,
genre and album art that is displayed to a user. A user can
subsequently purchase the album in various quantities and at
different unit prices depending on specials on offer. A user’s
purchase order will contain the date of purchase, their contact
details (address, telephone and/or email) and the total price.
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OrderDetail
Album
PK
OrderDetailId
PK
AlbumId
FK1
FK2
OrderId
AlbumId
Quantity
UnitPrice
FK1
FK2
GenreId
ArtistId
Title
Price
AlbumArtUrl
Order
PK
OrderId
Date
Username
Name
Address
Phone
Email
Total
Genre
PK
GenreId
Name
Description
Artist
PK
ArtistId
Name
WHERE do we use data models?
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WHEN would a Business Analyst
use data models?
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Data Model Levels
Conceptual
Logical
Physical
How do we data model?
• People
• Business, users, developers, DBAs
• Inputs
• Business & functional requirements, business processes,
databases, documents, UI screens
• Tools
• Drawing packages (e.g. PowerPoint, Visio), data
modelling packages (e.g. ERWin, System Architect)
Entity Relationship Model
• Most common data modelling technique
• Used in most business information system development
• Tools that engineer a database from a data model
ER Process
1. Identify entities
2. Identify attributes
3. Identify relationships
4. Apply naming conventions
5. Assign keys
6. Normalise
Identify entities
• An object that exists and is distinguishable from other
objects
• Examples: person, company, event, place
• Should be a singular concept
Entity
Name
Person
Chair
Entity
Name
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Identify attributes
• Properties of an entity
Person
Attribute
Name
First Name
Last Name
Email Address
Chair
Colour
Height
Price
Attribute
Name
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Identify relationships
• An association between two entities
• Cardinality and optionality
• One to one
Person
• One to many
Chair
Person
Table
• Many to many
Phone
Number
Person
• Roles
Person
Person
Person
Phone
Number
Phone
Number
Chair
sits on
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Apply naming conventions
Examples:
• Singular vs plural names for entities
• Consistent names: date, summary, description, name
• Reference Types all ending with Type
• Standardise suffixes: Id, Key, Code, Flag
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Assign keys
Primary
Key
Person
PK
Natural
Key
Foreign
Key
FK1
Tax File Number
First Name
Middle Names
Last Name
Address Id
Address
PK
Address Id
Address Line 1
Address Line 2
Suburb
State
Post Code
Primary
Key
Surrogate
Key
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Normalise
• Every non-key attribute in every table is directly
dependent on the key
• Results in:
• Elimination of redundancies
• Fewer anomalies
• Most information systems are in third-normal form
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Scenario 1
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Scenario 1 – A Possible Data Model
Electrical Incident
Location
Incident
Location Id
Name
Incident Date
Summary
Description
Dangerous Event Flag
Reported By
Supervising
Officer
Environmental Incident
Investigation
Investigator
Person Type
Motor Vehicle Incident
Person
Bodily Location
Bodily Location Type
Injury/Illness Incident
Description
Person Id
Classification
First Name
Last Name Person Injured/Ill
Nature
Nature Type
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Scenario 2
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Scenario 2 – A Possible Data Model
Asset Type
Segment
Installation History
Agent
Install Date
Uninstall Date
Model
Asset
Product Family
Revision Number
Manufacturer
Serial Number
Attribute Type
Attribute
Unit Type
Value
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Data Model Patterns
David Hay – Data model patterns: Conventions of thought
Martin Fowler – Analysis patterns: Reusable object
models
Len Silverston – The data model resource book: A library
of universal data models for all enterprises
An Introduction to Data Modelling
Entity Relationship Modelling
Avin Mathew
amathew@smsmt.com
Nov 2010