cse3180 summer 2005 lect 2 / 1 lecture 2 project planning and control database design logical data...

CSE3180 Summer 2005 Lect 2 / 1

Lecture 2Lecture 2

Project Planning and Control

Database Design

Logical Data Modelling

and - Mulga Bill


Lecture 2Lecture 2

• Yesterday, we touched on the concept of a Project Plan

• This leads to Project Planning and Control

• So for the next few minutes, we will be overviewing this important feature of ANY project.

• And then we will move onto Database Design


Project PlanningProject Planning

• Planning• Scheduling• Cost Tracking• Resource Management• Reporting

Software FunctionsReal time interactive operationAdd / Delete itemsChange logic dependencies

Adjust calendar and calendar dependenciesChange resource and availability levels and datesMouse driven : Multiple platforms

(Microsoft, MacIntosh)


Project Planning and ControlProject Planning and Control

Part of the ‘project’ you will complete will be subject to Project Planning.

One member of each group will become responsible for administering the resources - time and personnel skills.

This person will be responsible that the 2 components are completed in the timescale and that the associated documents are complete

The following overheads give you some idea of the scope of this very important component of ANY project


Project PlanningProject Planning

1. Project Manager’s Controls - Schedule

- Costs

- Technical

- Resources

2. Goals, Objectives, Targets, Disciplines

3. Development of Project Definition / Scope

4. Performance Assessment Criteria

5. Level of Detail in Planning

6. Feed back and Controls

7. Replanning and Rescheduling

8. Budgeting


Project Planning - Gannt ChartProject Planning - Gannt Chart

Task / Week 1 2 3 4 5 6 7Analysis

Design

Review

Programming

Implementation

- Plan

- Manuals

System Testing

Review

Acceptance Test

Review Results

Handover


PERT DiagramPERT Diagram

start

Get Mix Pour intoingredients Ingredients cake pan

Preheatoven

Place Bake Removecake in cake cake fromoven oven


Data Base DesignData Base Design


Data Base DesignData Base Design

· Reduce data redundancy.

· Provide stable data structures that can be readily changed with changing user requirements.

· Allow users to make ad hoc requests for data.

· Maintain complex relationships between data elements.

· Support a large variety of decision needs

Hawryszkiewycz I J (1984) Database Analysis and Design p 2


End Product of Data Base DesignEnd Product of Data Base Design

A database which will:

• Accurately reflect the ‘real world’ data in all required aspects

• Be responsive to Management information demands

• Reflect Business Rules and Controls

• Be capable of modification to meet changes in Management needs

• Be an asset to the Organisation/Enterprise


Business Functions and ProcessesBusiness Functions and Processes

• Business Functions :

Broad groups of closely related activities and decisions which contribute to a product or service like cycle. (e.g. planning, materials management, production planning, quality assurance).

• Business Processes : Decision related activities which occur within a function. They are related to management of people, money, material and information.

Materials Management (Business Function)could be

subdivided into: requirements planning, purchasing, goods

received, material accounting, stockkeeping

Business Processes should reflect related activity groupings


Business ActivitiesBusiness Activities

Business Activities : Specific operations or transactions

required to carry out a process

Some guidelines:

An activity should produce some clearly defined (identifiable) result - a product, a decision, a plan ......

An activity has clear boundaries - a clear beginning and end. Activities do not overlap.

An activity is carried out as a unit, by a single agent or a team

Once initiated, an activity proceeds independently of and from other activities.


Business EntitiesBusiness Entities

Are persons, objects or events about which Information is, or will be, recorded in the Information Data Base

Many of these Entities can be identified with Business Activities (e.g. suppliers, purchase orders, customer)


Critical Success FactorsCritical Success Factors

* Key factors which must be performed well to ensure the success of an organisation

* Also known as Key Performance Indicators (KPIs)

e.g. production failure rate < 0.01% of total production units

production cost increases <= c.p.i. increases

customer service complaints < 1% of all customer transactions (relates to later lecture)

absenteeism < 1% of staff in any 24 hour period

product quality => advertised standards (water, power)

% of students successful in their Degree course

% spread of results - %HD, %D, %N


Design CriteriaDesign Criteria

- data availability

- data reliability

- data currency

- data consistency

- data flexibility

- data efficiency

Verify these criteria are satisfied via the technical review


Database DesignDatabase Design

- the process of developing database structures from user requirements for data

- a structured methodology

Structured Methodology - a number of ordered formalprocesses with known inputs and expected outputs

Objectives

1. derive relationships2. evolve to meet user requirements3. user requests are met within reasonable time limits


3 Schema Architecture3 Schema Architecture

The Primary Objectives of a DBMS are to providefacilities for :

1. Definition of Database Logical Structures

2. Definition of Physical Structures

3. Access to the Database

4. Definition of Storage Structures to store user data

These components are known as the ‘database architecture’


3 Schema Architecture ANSI - SPARC Architecture3 Schema Architecture ANSI - SPARC Architecture

EXTERNALSCHEMAS

CONCEPTUALSCHEMA

INTERNALSCHEMA(Storage Views)

user 1 user 2 user..nlogical

logical

physical

(as seen by database analysts, designers, programmers and the Data Base Administrator)

(as seen by the Operating System and the Data Base Administrator)

SCHEMA: Describes data in the data base - also sub-schema

Global


3 Schema Architecture3 Schema Architectureexternal external external external view A view B view C view X Cobol C Assembler External+ DML + DML DML + DML Schemas

dbms Conceptual Model Conceptual Schema

Internal Model Internal Schema

Physical Level

userinterface

logicalrecord

interface

storedrecord

interface

physicalrecord

interface

operatingsystem



FunctionalRequirements

Information Level Design Processes

Final InformationLevel Design

PhysicalConstraints

PhysicalLevel Design

Other mattersDomains, Nulls, Derived Data,Encoded Data.

Data Base Model

Final DatabaseStructure


e-mailfiles


4th Generation Environment - User Perception

user terminal

teleprocessing report query electronicmonitor writer language mail

applicationprograms

data dictionaryDBMS

database

structured and non-structured dataimages, graphics, video,voice


Data ModellingData Modelling

Some Terms and Considerations MEDIA : Magnetic Disks, Optical Disks, CD Roms, Other devices (Smart Cards)

TERMS : Seek Time, Rotational Delay, Cylinder, Track, Sector, Block, Page, Device

ACCESS TIMES ~ 400ms or less - floppy disk 23 to 30 ms or less large fast disk AIM OF Storage Structures and DBMS : To reduce the number of I/O’s

STORAGE STRUCTURE : An arrangement of data on a storage medium

Data Access Software 1. Disk Manager (page level) 2. File Manager (record level)


Some More TermsSome More Terms

Types of TablesBase Table : A stored table. A physically persistent table, stored as a file on disk when implemented in a relational database management system

Derived Table : A temporary table produced as a result of a query on one or more base tables, or the invocation of a view. A derived table exists for the duration of the operation which creates it . ( a question : where does it exist ?)

View : A virtual table - stored as a query which when invoked generated a derived table. This view can then be queried as if it were another base table. (we will discuss views later in the semester)


Data ModellingData Modelling

Data Modelling is about - Structuring and Organising Data

Leads to the emergence of Records Attributes Data Types Constraints Semantics e.g. age relates to ? person ? building ? isotope ? galaxy ?

Commercial Data Base ModelsHierarchical Specific organisation and relationships between records held in the databaseNetwork Relational Constraints, domains, conditions of update, inserts, deletes, modifications, access


EntitiesEntities

• The designation of a ‘thing’ about which data is to be collected

stored

processed

• Typical Entities : persons, items, buildings, stocks,

vehicles, jobs, books, libraries


Entity RelationshipsEntity Relationships

Type Shown As Example

1. One to One 1:1 Driver -----> Licence Watch For :

OPTIONAL

2. One to Many 1:M Subject ---------> Students MANDATORY

3. Many to Many M:N Order <------------> Part Number

Order No. Part No.

1 A

2 B

3 C

4 D

Create Order-Part record

Or, The Relationships between Entities


Logical Data ModellingLogical Data Modelling

• 3 types of data objects:– Entities– Attributes– Relationships

• ENTITIES: Are persons, places, or things about which data is to be, or is, gathered

• ATTRIBUTES : Are the properties of entities

Examples are Names, Tax Numbers, Age, Status• RELATIONSHIPS : Describe how entities relate to each other

e.g. Customers BUY Products

Persons WORK_ON Jobs



Entity-Type : An entity type represents the class of Objects which share some common aspect -

such as Jobs, Persons, Materials, Houses

Entity-Occurrence : Also called ‘entity instance’

Example : “3 bedroom, brick veneer, 10 years old” are some of the actual values of an

entity instance of the Entity Type ‘House’

A common term for this is ‘real values’



CARDINALITY

Premise: If an entity ‘A’ relates to another entity ‘B’, then the conditions of occurrences of ‘A’ and ‘B’ need to be known.

CARDINALITY : The specification of the number of occurrences of 1 entity type which can be related to the

number of occurrences of another entity type

Cardinality is expressed as ‘one’ or ‘many’



2 entities can be related as :

One to One : (1 : 1)

The interpretation of this is that an occurrence of an entity ‘A’ can relate to ONE and ONLY ONE occurrence of entity ‘B’, and an occurrence of entity ‘B’ can relate to ONE and ONLY ONE occurrence of entity ‘A’

One to Many : (1: M) or (1 : N)

The interpretation is that ONE occurrence of entity ‘A’ can relate to ONE or MORE occurrences of entity ‘B’, but an occurrence of entity ‘B’ can relate to ONE ONLY occurrence of entity ‘A’



Many to Many (M : N) - a common business relationship

The interpretation is that ONE or MORE occurrences of entity ‘A’ can relate to ONE or MORE occurrences of entity ‘B’ and ONE or MORE occurrences of entity ‘B’ can relate to ONE or MORE occurrences of entity ‘A’

Is this the relationship which you are dealing with in Part 2 of your assignment ?



One to One

One to Many

Many to One

Many to Many


Entity Relationships Entity Relationships

• Students have a M : 1 relationship with a Course

• A Course has a 1 : M relationship with prescribed units

• A Unit has a 1 : M relationship with Students



MODALITY

An extension of relationship

Indicates whether an occurrence MUST PARTICIPATE in a relationship

Cardinality indicates the maximum number of entity occurrences which can participate in a relationship

Modality indicates the minimum number of occurrences

Modality = 0 if an occurrence is not needed or is optional

Modality = 1 if an entity occurrence is required or mandatory



DEGREE

Relates to the number of entity types associated in a relationship

UNARY - The entity type is related only to itself (also called recursive)

BINARY - Two entity types are related (most common case)

TERNARY - A relationship involving more than two entity types



ATTRIBUTE TYPES and ATTRIBUTE VALUES

An attribute type is an occurrence of a named set of values

e.g. ‘size’, ‘name’, ‘mass’, ‘person_id’

An attribute value is an occurrence (or instance) of an attribute type

An attribute value is a characteristic of, or a fact about an entity occurrence

e.g. Attribute ‘size’ Attribute value ‘25.4mm’

Entities/Attributes are often referred to as ‘meta-data’, that is ‘data about data values’



DOMAINS

A ‘Domain’ is a set of possible values which an attribute set can adopt

e.g. dates, integers, person name constructions, post codes

3 Main Types of Domains:

Data Type : Numeric, Text, Integer, Date .....

Ranges : Values between sets

‘Employee numbers must be between 10156 and 10987’

Acceptable Values : Specific Post Codes, Area Codes,

Names of Prominent People, Building Names

They indicate the only values an attribute can have.

All of these features contribute to ‘Database Integrity’


Logical Data Modelling Logical Data Modelling

seamenSalesRep Customerrepresents

Relationships Representation

Order PartAssociated with



Cardinality

Meaning : ONE Meaning : MANY

Course Units



Cardinality

Meaning : ONE Meaning : AT LEAST ONE or MANY

Course Units

Many means more than One



Mandatory - Optional Relationship

Artists paint Pictures

Unary Relationship

(BinaryRelationship)

Ternary Relationshipcustomers cars

dealers

buy



ENTITIES

RELATIONSHIPS

ATTRIBUTES

membership class

degree

domains

values

cardinality

modality

recursive

binary

n-ary

1 : 11 : NM : N

mandatory

optional



part

vendorwarehouse

quantity

ships

Quantity is the amount of a particular ‘part’ delivered from a particular‘vendor’ to a particular ‘warehouse’.

Each entity may be a ‘one’ or‘many’ participant


The Monash GalleryThe Monash Gallery

Exhibition Carrier

Contact

ArtistHistory

Gallery

ExhibitionCategory

Contract CollectionBuyer

Invoice

Payment

ItemArtist

ArtistCategory

Category


Model InterpretationModel Interpretation

What do these models indicate ? Are they accurate ?

Student ? Course

Library Texts,Periodicals

Borrowers

Aircraft Flight Passenger

?

Maintenance


Data Modelling ThoughtsData Modelling Thoughts

Nation Stock

nation code stock codenation name firm nameexchange rate stock price stock qty

stock divdnd

A 1:M relationship

Entities

Attributes



Nation State City

Name Statename Cityname Population Statepop Citypop Area State area City Area

Questions : Is the Nation ‘Population’ necessary ? Is the State ‘Population’ necessary ?



Library Book Borrower

libname callno borrower ID ISBN booktitle duedate

Library Book Copy Borrower

libname callno bookno borrowerID ISBN due date title

Physical Objects



An interesting data model can be constructed which deals with aircraft leasing;

An aircraft broker will ‘own’ many aircraft which will be leased to a variety and number of airline companies (including of course Virgin Blue and Qantas)

When a lease expires, the broker leases the plane to another airline company, which explains why there are some aircraft still flying which are 20 to 30 years old.

In this scenario, an aircraft can be leased many times, and an airline company can lease many aircraft.

Normally there is an agent handling each such deal. An agent can lease many aircraft and deal with many airlines. A transaction occurs when a deal is reached with an airline to lease an aircraft or a number of aircraft.


Modelling the Aircraft ScenarioModelling the Aircraft Scenario

Aircraft Aircraft- Agent Agent

aircraft code Agent ID

Airline- Airline Airline-Aircraft Agent

airlinename

An Aircraft - Airline - Agent data model



There is a bit of a problem here.

Where is the data relevant to the lease to be stored ( and how many times, and therefore how many versions ? - and which of these is the correct current value ?)

It could be in Airline-Aircraft.

If so, the agent responsible for the deal is ignored. Should it be in Agent-Airline ?

What is the problem here ?



• A solution:

Aircraft Lease Agent

aircraftcode start date agentid

Airline

Airlinename


Business SystemsBusiness Systems

Many Business Information Systems incorporate a database or many databases in their construction

The database(s) must be able to respond to ‘normal’ processes such as update, regular reports, regular queries as well as support new queries, drill down information requests as well as being robust enough to accommodate organisational, reporting and ‘emergency’ conditions.

The ‘main’ database is often imaged onto another server for access by organisational departments, functional managers and for special planning. Such database ‘copies’ are rarely updatable or have feedback capability to the main enterprise database(s)


Database Development ProcessesDatabase Development ProcessesDatabase Development ProcessesDatabase Development Processes

Project Identification Selection

Project Initiation and Planning

Analysis

Logical Design

Physical Design

Implementation

Maintenance

Plus Reviews


Have you heard this before ?Have you heard this before ?

A relation is a named table with columns and rows

An attribute is a named column of a relation

The domain of an attribute is the set of values the attribute may take

A tuple is an alternative term for a row of a relation

The number of attributes is known as the degree of a relation

The number of rows is known as the cardinality of a relation


Mulga Bill’s Bicycle - Banjo Patterson


Twas Mulga Bill, from Eaglehawk, that caught the cycling craze;

He turned away the good old horse that served him many days;

He dressed himself in cycling clothes, resplendent to be seen;

He hurried off to town and bought a shining new machine;

And as he wheeled it through the door, with air of lordly pride,

The grinning shop assistant said, “excuse me, can you ride ?”




“See here young man” said Mulga Bill “from Walget to the sea,

From Conroy’s Gap to Castlemaine, there’s none can ride like me.

I’m good all round at everything, as everybody knows,

Although I’m not the one to talk - I hate a man that blows.

But riding is my special gift, my chiefest, sole delight;

Just ask a wild duck can it swim, a wild cat can it fight.

There’s nothing clothed in hair or hide, or built of flesh or steel,

There’s nothing walks or jumps or runs, on axle, hoof or wheel,

But what I’ll sit, while hide will hold and girths and straps are tight

I’ll ride this here two-wheeled concern right straight away at sight”




T’was Mulga Bill, from Eaglehawk, that sought his own abode,

That perched above the Dead Man’s Creek, beside the mountain road.

He turned the cycle down the hill and mounted for the fray

But ere he’d gone a dozen yards it bolted clean away.

It left the track, and through the trees, just like a silver streak,

It whistled down the awful slope, towards the Dead Man’s Creek.




It shaved a stump by half an inch, it dodged a big white-box

The very wallaroos in fright went scrambling up the rocks

The wombats hiding in their caves dug deeper underground,

As Mulga Bill, as white as chalk, sat tight to every bound.

It struck a stone and gave a spring that cleared a fallen tree,

It raced beside a precipice as close as close could be:

And then as Mulga Bill let out one last despairing shriek

It made a leap of twenty feet into the Dead Man’s Creek




T’was Mulga Bill, from Eaglehawk, that slowly swan ashore:

He said “I’ve had some narrer shaves and lively rides before

I’ve rode a wild bull round a yard to win a five pound bet,

But this was the most awful ride that I’ve encountered yet.

I’ll give that two-wheeled outlaw best; it’s shaken all me nerve

To feel it whistle through the air and plunge and buck and swerve.

It’s safe at rest in Dead Man;s Creek, we’ll leave it lying still;

A horse’s back is good enough henceforth for Mulga Bill”


That should be enough for today - see you tomorrow.

cse3180 summer 2005 lect 2 / 1 lecture 2 project planning and control database design logical data...

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