IMS 5024

Data Modelling (1)

IMS 5024 Lecture 3 2

Content

Individual assignment date Pitfall revisited Group assignment Class assignment Nature of data modelling Tools/Techniques used in data modelling Place in ISD Evaluation of data modelling Reading list

Date for the individual assignment Two dates appear in the hand out:

– 23 August 2001– 27 August 2001 (it also wrongly states that

it is a Friday)

What will it be!!!

–27 August 2001 at 17h00!!

Class assignment

What is this about?

What conventions/rules are used?

What does it depict?

Where would this fit into ISD?

Data modelling describe:

Structure Meaning Relationship

Of Data

Data modelling help us to grasp:

Static Data in the organisationFundamental building block of

the systemTwo perspectives (Process and

Data)

Techniques used in Data modelling Entity relationship diagrams Normalisation Data Dictionary

What difference? Use both?

Entity

Entity – things of interest to the business

Identification of an entity is subjective Entities can be:

• Real eg product• Abstract eg Quota• Event remembered eg sale• Role played eg employee

Employee

Relationship

Relationship Between entities

Cardinality (eg. One to many, one to one ect.)

Degree of relationship (Unary, Binary, Ternary)

DepartmentEmployee

Examples of Cardinalities

PATIENTHISTORY

PATIENT

PROJECT

EMPLOYEE

PERSON

Mandatorycardinalities

Optional and mandatorycardinalities

Optionalcardinalities

Has

Is assigne

d to

Is married

to

Relationship Cardinality Summary

Mandatory 1 cardinality

Many cardinality (1,2 …m)

Optional (0 or 1) cardinality

Optional (0 or many) cardinality

Unary Relationship

Also called a recursive relationship

PERSON EMPLOYEE

One to manyOne to one

Ismarried

to

Manages

Binary Relationship

A binary relationship is a relationship between instances of two entity types.

PROJECT

EMPLOYEE

SALESORDER

CUSTOMER

ITEM

SUPPLIER

One to one One to many Many to many

Leads PlacesSupplie

s

Ternary Relationship A ternary relationship is a relationship

between instances of three entity types.

PART

suppliesVENDOR CUSTOMER

Attributes

What we want to know about the entity or a relationship

Types:– Derived,– multi-valued, – Composite,– Simple

Example of attributes

EMPLOYEE

Emp-no

Name Address

Skill

Supertypes and subtypes

Benefits:– Presentation– Creativity– Communication– Classifying common patterns– Divide and conquer

Generalisation vs Specialisation

Example of super- and subtypes

EMPLOYEE

Emp-no

Name Address

Skill

HOURLYEMPLOYEE

SALARIEDEMPLOYEE

CONSULTANT

Contract numberStock optionHourly rate

Annual salary

Billing rate

Thinking in Data modelling

Hard Vs Soft ?? Perspective

– Objective vs Subjective– Nature of the organisation

Evaluation of Data modelling

Problem oriented Product oriented

Concep-tual

Structured analysis

Entity relationship modelling

Logical construction of systems

Modern structured analysis

Object oriented analysis

Structured design

Object oriented design

Formal PSL/PSA

JSD

VDM

Levels of abstraction

Stepwise refinement

Proof of correctness

Data abstraction

JSP

Object oriented programming

Advantages of Data modelling

Data model is not computer oriented (agree??) Model understandable by technologist and

users Does not show bias UoD can vary (whole organisation or

department) Readily transformable into other models Different data analysis techniques Data modelling is rule-based

Disadvantages

Does not encourage/support user participation

Your view on the organisation –people or data

The idea that the model is THE model Subjective view One-side ito data Others??

Process modelling view of ISD

Development group

Objectives

Environment

Object system

ObjectsystemChange

process

Hirschheim et al see reading list

Reading for next week

Simsion, G. (1994). Data modeling essentials: Analysis, Design, and Innovation. Van Nostrand Reinhold, USA. Chapter 2, 7 and 10.