49959953 Data Flow Diagram

8/12/2019 49959953 Data Flow Diagram

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Data Flow Diagrams(DFDs)


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Data Flow Diagrams (DFDs)

Data flow diagram(DFD) is a picture ofthe movement ofdata betweenexternal entities andthe processes anddata stores within asystem

1.0

Chec!tatus

".0

#ssue!tatus

$essages

C)!+'$,-

.0

$anage (ccounts-eceivable

'rder #n3!toc -e4uest

!tatus Data

!tatus$essage

2ending'rdersD1

'rderData

'rder Data

!hippingConfirmation

#nvoice

2ayment

(ccounts-eceivableD"

(ccounting Data (ccounts -eceivable Data

'rder Data

#nventory-eports


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DFD !ymbols (&ane 5 !arson)

2rocess

Data Flow

Data !tore

!ource6!in (,xternal ,ntity)


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2rocess

or or actions performed on data (inside the system)7abels should be verb phrases-eceives input data and produces output

1.0

2roduce&rade-eport

&rade Detail &rade -eport


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-ule 18 2rocess

Can have more than one outgoing data flowor more than one incoming data flow

1.0

&rade!tudent

or

!ubmitted or &raded or

!tudent &rade

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Calculated&ross

2ay

/ours ored

2ay -ate&ross 2ay


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-ule "8 2rocess

Can connect to any other symbol (including anotherprocess symbol)

1.0

9erify'rder

".0

(ssemble'rder

'rder (ccepted 'rder #nventoryChange


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2rocess8 Correct6#ncorrect:.0

Create#nvoice

!ervices 2erfomed #nvoice

(pply#nsurance2remium

2ayment (mount2olicy *umber

".1

Calculate&ross

2ay

/ours ored 2ay -ate


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Data Flow

#s a path for data to move from one part of the #!to another

rrows depicting movement of dataCan represent flow between process and datastore by two separate arrows

Deposit

".1

2ost2ayment

(ccounts-eceivable

D1

2ayment Detail

#nvoice Detail


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Data Flow8 Correct6#ncorrect:

Courses

!tudents

Class7ist

.0

2ost2ayment

Customer2ayment

D" Daily 2ayments

;.0

2repareDeposit

Daily2ayment


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-ule8 Data !tore

$ust have at least one incoming and oneoutgoing data flow

Daily2ayments

D1

Customer 2ayment

Daily 2ayment


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Data !tore8 Correct6#ncorrect:

".0


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!ource6!in (,xternal ,ntity)

,xternal entity that is origin or destination of data (outside the system)

#s the singular form of a department= outside organisation= other #!= or person7abels should be noun phrases

C)!+'$,-

1.0

9erify'rder

'rder #nvoice

!ource > ,ntity that supplies data to thesystem!in > ,ntity that receives data from the

system


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-ule8 !ource6!in$ust be connected to a process by a data flow


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!ource6!in 8 Correct6#ncorrect:

2(@-'77D,2(-+$,*+

,$27'@,,

2aychec

%.0

(pply2ayment

C)!+'$,-

2ayment

C)!+'$,-

(ccounts-eceivable

2ayment


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-ules for sing DFD !ymbols

Data Flow +hat Connects@,! *'

process to another process

process to an external entity

process to a data store

n external entity to another external entity

n external entity to a data store

data store to another data store


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7ist the errors of this DFD

,1

2"

2

1.0

".

D!1

DF "

DF"

DF;

DF

DF1

DF


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Context Diagram

+op3level view of #!!hows the system boundaries= external entities thatinteract with the system= and maAor information flows

between entities and the system.,xample8 'rder system that a company uses toenter orders and apply payments against acustomerBs balance


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0

'rder!ystem

!(7,!-,2

C)!+'$,- (-,/')!,


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7evel30 DFD

!hows the systemBs maAor processes= data flows=and data stores at a high level of abstractionhen the Context Diagram is expanded into DFD

level30= all the connections that flow into and out ofprocess 0 needs to be retained.


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0

'rder!ystem

!(7,!-,2

C)!+'$,- (-,/')!,


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1.0

Fill'rder

".0

Create#nvoice

%.0

(pply2ayment

C)!+'$,- (-,/')!,

'rder

'rder-eAect*otice

2icing 7ist

(ccounts-eceivableD1

#nvoice

#nvoice

#nvoiceDetail2ayment

Detail

2ayment

Commission


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!trategies for Developing DFDs

+op3down strategyCreate the high3level diagrams (ContextDiagram)= then low3level diagrams (7evel30

diagram)= and so on


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#dentify ,ntities=2rocess=Data !tores 5 Data Flow,ntities

Customer arehouse

ccounting

2rocesses1.0 Chec !tatus

".0 #ssue !tatus $essages%.0 &enerate !hipping 'rder .0 $anage ccounts -eceivable.0 2roduce -eports

Data !toresD1 2ending 'rdersD" ccounts -eceivable

Data Flows'rder #n3!toc -e4uest'rder Data!tatus Data

!tatus $essage!hipping 'rder 'rder Data#nvoice!hipping Confirmation2ayment

ccounting Data ccounts -eceivable Data'rder Data

#nventory -eports

1.0

".0

%.0

.0

.0


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(CC')*+#*&

(C)!+'$,-

0

'rder!ystem

'rder

2ayment#n3!toc-e4uest

!tatus

$essage

#nvoice !hipping Con

!hipping

'rder

#nventory-eports

ContextDiagram of'rder!ystem


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1.0

Chec!tatus

".0

#ssue!tatus

$essages

%.0

&enerate!hipping

'rder

C)!+'$,- (-,/')

.0

$anage (ccounts-eceivable

.0

2roduce-eports

'rder #n3!toc -e4uest

!tatus Data

!tatus$essage

2ending'rdersD1

'rderData

'rder Data

!hip'rde

!hippingConfirmation

#nvoice

2ayment

(ccounts

-eceivableD"

(ccounting Data (ccounts -eceivable Data

'rder Data

#nventory

7evel30 of'rder !ystem


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Decision +rees


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Decision Trees


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Planning Tool


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Decision +rees

,nable a business to 4uantify decisionma ingseful when the outcomes are uncertain

2laces a numerical value on li ely orpotential outcomes llows comparison of different possibledecisions to be made


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Decision +rees

Limitations:/ow accurate is the data usedin the construction of the tree:/ow reliable are the estimatesof the probabilities:Data may be historical > does this data relate to realtime:*ecessity of factoring in the 4ualitative factors >

human resources= motivation= reaction= relations withsuppliers and other sta eholders


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Process


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+he 2rocess

Expand by opening new outlet

Maintain current status

Economic growth rises

Economic growth declines

0.7

0.3

Expected outcome300 000

Expected outcome!"00 000

0

s4uare denotes the point where a decision is made= #n this example= a business is contemplatingopening a new outlet. +he uncertainty is the state of the economy > if the economy continues to growhealthily the option is estimated to yield profits of %00=000. /owever= if the economy fails to grow asexpected= the potential loss is estimated at 00=000.

+here is also the option to do nothing and maintain the current status 4uo +his would have an outcome of0.

+he circle denotes the point where different outcomes could occur. +he estimates of the probability and thenowledge of the expected outcome allow the firm to ma e a calculation of the li ely return. #n thisexample it is8

,conomic growth rises8 0.E x %00=000 "10=000

,conomic growth declines8 0.% x 00=000 3 1 0=000

+he calculation would suggest it is wise to go ahead with the decision ( a net GbenefitB figure of H ;0=000)


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The Process

Expand by opening new outlet

Maintain current status

Economic growth rises

Economic growth declines

0."

0."

Expected outcome300 000

Expected outcome!"00 000

0

7oo what happens however if the probabilities change. #f the firm is unsure of the potential for growth= itmight estimate it at 08 0. #n this case the outcomes will be8

,conomic growth rises8 0. x %00=000 1 0=000

,conomic growth declines8 0. x 3 00=000 3 " 0=000

#n this instance= the net benefit is 3 100=000 > the decision loo s less favourable


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#d$antages


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Decision +ables


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$odeling 7ogic with Decision +ables

matrix representation of the logic of adecision!pecifies the possible conditions and theresulting actions


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$odeling 7ogic withDecision +ables

Consists of three partsCondition stubs

7ists condition relevant to decision

ction stubs ctions that result from a given set of conditions-ules

!pecify which actions are to be followed for a

given set of conditions

$ d li 7 i i h


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$odeling 7ogic with Decision +ables

#ndifferent ConditionCondition whose value does not affect which action ista en for two or more rules

!tandard procedure for creating decision tables*ame the condition and values each condition canassume*ame all possible actions that can occur 7ist all rulesDefine the actions for each rule!implify the table


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Figure I3Complete decision table for payroll system example

I. %I. %


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Constructing a Decision +able

2 -+ 1. F- $, +/, 2-'


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,xample

Calculate the total cost of your tuition this4uarter.

hat do you need to now:7evel. ( ndergrad or graduate)!chool. (C+#= 7aw= etc.)!tatus. (Full or part time)*umber of hours

ctions:


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ctions:Consider C+# only (to ma e the problem smaller)8

6&2art +ime (1 to 11 hrs.)8 00.006per hour Full +ime (1" to 1J hrs.)8 10000.00K Credit hours over 1J are charged at the part3time rate

&raduate82art time (1 to E hrs.)8 "0.006per hour Full time (L J hrs.)8 "0.006per hour

Create a decision table for this problem


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,ntity -elationshipDiagrams


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JI. JI. J


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Conceptual Data

$odeling=,3- Diagrams

49


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#mportance of Conceptual Data $odeling

Data rather than processes are more complex in many moderninformation systems.

Characteristics of data (structure= properties) are more stable=i.e. less li ely to change over time= easier to reach consensus on.

#t is shared between many processes= therefore is crucial in thedesign of databases= ensuring integrity of the data in aninformation system= efficiency of processing.

0


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'utline

2urpose and importance of conceptualdata modeling,ntity3-elationship $odel

,ntity ttributes

-elationships

1


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An Entity

!omething of interest in the environment (e.g.= person=place= obAect= event= concept)-epresented in ,3- diagram by a rectangle

n instance is a particular occurrence of an entity

CUSTOMER

Entity, or Entity Type

0010

Scott George56 Neat StreetBoulder, Colorado5!!"#"$%%50$#"% #!$&%

'n (n)tance o* t+e Cu)to er Entity"


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Entities

Entity Type 3 a collection of entity instancesthat share common properties (also simply calledan Entity )

Entity Instance 3 an individual occurrence ofan entity type

%


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Example Entity & Instances

Cu)t-(. /a)t-Na e ir)t-Na e 'ddre)) City ST ip

0001 Snerd Morti er General .eli2ery Ta pa / 6&$000" ogg Bo3 56$ ogg /ane O a+a NE "&05000 ' o) a ou) " Coo4ie Ct Mia i / 1000& Targa Ma ine 6$ a)t /ane Clinton N7 "00!"0005 George Scott 56 Neat St Boulder CO 5!!"0006 Guy Nice "%0 8lea)ant St Ta pa / 6&1000$ S it+ Bo3 $6 9ua4er 8at+ :ynn N; "111!000% S it+ 7a e) " & Bay2ie< Ta pa / 6&1

(denti*ier 'ttri3ute


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p g g

;


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hat !hould an ,ntity


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(nappropriate entitie)igure #&


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Sy)te u)er Sy)te u)er Sy)te outputSy)te output

'ppropriate entitie)

igure #&

I


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An Attribute

discrete data element characteristic (property) of an entity

CUSTOMER Cu)to er-Nu 3er /a)t-Na eir)t-Na eStreet-'ddre))

CityStateip8+one

This Customer entityhas eight attributes

;0


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Types of Attributes

!imple vs. Composite !imple 3 most basic levelComposite > decomposable into a group of related attributes

ex8 address (street= city= state= Oip)

!ingle 9alued vs. $ulti 9alued >!ingle 3 only one value per entity instance (e.g.= last name= date ofbirth)$ulitvalued3 multiple values per entity instance (e.g.= degrees= clubs=

s ills)!tored vs Derived (e.g . Date'f


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ttributes on ,-Ds

$ay be shown on ,-Ds as ellipses

8?;S(C('N 8'T(ENTS'd it) 0

e p#id

na e addre))

pt#nu

na e


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ttributes on ,-Ds

Multivalued attributes are shown as double ellipses

EM8/O;EE

e p#id

na e)4ill)

*-na e

l-na e

-na e

Multi2alued co po)ite

Composite attributes may be shown bro en downinto their simple components

Si ple@Single Aalued 8ri ary ey

;%


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+extboo Bs notation

;;

'n attri3ute 3ro4eninto co ponent

part)

$ultivaluedan employee can havemore than one s ill

Derivedfrom dateemployed andcurrent date


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Identifiers/Primary Key

Every instance of an entity must be uni4uely identified (tounambiguously distinguish them)

n identifier can be one or more attributes called acomposite identifier (e.g.= first name= middle name= and last name)

Partial identifier (in weak entities) > attribute that togetherwith some attribute from another entity identifies an

instanceUnderline identifiers in diagrams

;


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Identifiers

$ust be uni4ue!hould not change value over time&uaranteed to have a valid value*o intelligent identifiers (e.g. containing locations or people that might change)Consider substitutingsingle3attributeidentifiers forcomposite identifiersto simplify design andenhance performance

CUSTOMER Cu)to er-Nu 3er /a)t-Na eir)t-Na e'ddre))CityStateip8+one;;


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Relationships

relationship is an association between one or moreentities

+he degree of a relationship indicates the number of entities

involved+he cardinality of a relationship describes the number ofinstances of one entity associated with another entity

;E


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;J

Figure %310 -elationship types and instances

a) -elationship

b) -elationshipinstances


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ardinality onstraints

0 Optional relation)+ip)

none or one0

0 none or ore

Mandatory relation)+ip)

one and only one

one or ore

;I

patient must haverecorded at least onehistory= and can have many

patient history isrecorded for one andonly one patient


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Cardinality Constraints

Cardinality Constraints 3 the number ofinstances of one entity that can or must beassociated with each instance of another entity.$inimum Cardinality

#f Oero= then optional#f one or more= then mandatory

$aximum Cardinality+he maximum number

E0


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!e"rees of Relationships: unary and binary

T+e nu 3er o* di**erent entitie) in2ol2ed in a relation)+ip

EM8/O;EE Manage) UN'R;

STU.ENT .ORM(TOR;() a))igned

B(N'R;

E1


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$ore on -elationships

-elationships (many3to3many or one3to3one) can have attributes+hese describe features pertaining to the association between the entities in therelationship

+wo entities can have more than one type of relationship between them(multiple relationships)

ssociative ,ntity combination of relationship and entity!ome typical cases

E%

E a ple) o* ultiple relation)+ip) entitie) can 3e


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E a ple) o ultiple relation) ip) entitie) can 3erelated to one anot+er in ore t+an one


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+ime stamping

E

ntities can be related to one another in more


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igure #"1a E ployee) and depart ent)

,ntities can be related to one another in morethan one way

E;

!trong vs ea ntities= and


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!trong vs. ea ,ntities= and#dentifying -elationships

!trong entitiesexist independently of other types of entitieshas its own uni4ue identifier represented with single3line rectangle

ea entitydependent on a strong entityPcannot exist on its ownDoes not have a uni4ue identifier represented with double3line rectangle

#dentifying relationshiplin s strong entities to wea entitiesrepresented with double line diamond

EE

i i i i


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ssociative ,ntities

ssociative entities provide details of a many3to3many association.#tBs anentity > it has attributes

*D itBs a relationship > it lin s entities together hen should a relationship with attributes instead be an associative entity :&uidelines8

ll relationships for the associative entity should be many+he associative entity could have meaning independent of the other entities+he associative may be participating in other relationships other than the entities ofthe associated relationship+he associative entity preferably has a uni4ue identifier= and should also have otherattributes.#f an associative entity may have a partial identifier.+ernary relationships should be converted to associative entities

EJ


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$odeling a ternary relationship as an


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$ode g a te a y e at o s p as aassociative entity

J0

#ntroduction to ,ntity3


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, y-elationship (,3-) $odeling

*otation uses three main constructsData entities-elationships

ttributes,ntity3-elationship (,3-) Diagram

detailed= logical representation of the

entities= associations and data elements foran organiOation or business

10.J110.J1

i 3 l i hi ( 3 ) $ d li


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,ntity3-elationship (,3-) $odeling?ey +erms

,ntity person= place= obAect= event or concept in the userenvironment about which the organiOation wishes tomaintain data-epresented by a rectangle in ,3- diagrams

,ntity +ype collection of entities that share common properties orcharacteristics

ttribute named property or characteristic of an entity that is ofinterest to an organiOation

10.J"10.J"

$


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Candidate eys and identifiers,ach entity type must have an attribute or setof attributes that distinguishes one instance

from other instances of the same typeCandidate ey

ttribute (or combination of attributes) thatuni4uely identifies each instance of an entity type

l


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,xamples

#dentify a few entity types= instances=attributes and candidate eys for8

De2aul Campus Connect -egistration !ystem

#llinois


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Depicting ,ntities and ttributes

Draw a portion of the ,-D for each of these systems8Campus Connect -egistration !ystem


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p gthe ,3- Diagram

&oalCapture as much of the meaning of the data as possible

#f you now the rules of normaliOation= referential integrity=foreign eys= etc.= this is good but not as important now. #tis much more important to get the organiOational datamodel correct= i.e. to understand the actual datare4uirements for the organiOation.

-esult better design that is scalable and easier to maintain

i 3 l i hi ( 3 ) $ d li


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#dentifier candidate ey that has been selected as the uni4ueidentifying characteristic for an entity type!election rules for an identifier 1. Choose a candidate ey that will not change its value". Choose a candidate ey that will never be null%. void using intelligent eys. Consider substituting single value surrogate eys for

large composite eys

i 3 l i hi ( 3 ) $ d li


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-elationship n association between the instances of oneor more entity types that is of interest to the

organiOation ssociation indicates that an event hasoccurred or that there is a natural linbetween entity types-elationships are always labeled with verbphrases

Cardinality


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Cardinality

+he number of instances of entity < that can beassociated with each instance of entity $inimum Cardinality

+he minimum number of instances of entity < thatmay be associated with each instance of entity +his is also called MmodalityN.

$aximum Cardinality+he maximum number of instances of entity < thatmay be associated with each instance of entity


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I0

I.I0I.I0

*aming and Defining


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-elationships-elationship name is a verb phrase

void vague names&uidelines for defining relationships

Definition explains what action is being ta en and why it isimportant&ive examples to clarify the action'ptional participation should be explained,xplain reasons for any explicit maximum cardinality

*aming and Defining


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-elationships&uidelines for defining relationships

,xplain any restrictions on participation in therelationship,xplain extent of the history that is ept in therelationship,xplain whether an entity instance involved ina relationship instance can transferparticipation to another relationship instance

10.I"10.I"

ntity


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,ntity

M n entity is a business obAect thatrepresents a group= or category of data.N 1

Do we now a similar concept:

1) !tephens= -.?. and 2lew. -.-.= "001. Database Design . ! $!= #ndianapolis = #*.

ttribute


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ttribute

M n attribute is a sub3group of informationwithin an entity.N 1

Do we now a similar concept:

1) !tephens= -.?. and 2lew. -.-.= "001. Database Design . ! $!= #ndianapolis = #*.


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$andatory= $any3to3$any


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$andatory= $any3to3$any

#*!+- C+'- !+ D,*+

#*!+- C+'- !+ D,*+

'ptional= $any3to3$any


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ptional= $any3to3$any

D,2 -+$,*+ !+ D,*+

D,2 -+$,*+ !+ D,*+

'ptional6$andatory=


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$any3to3$any

#*!+- C+'- !?#77

#*!+- C+'- !?#77

'ptional6$andatory=


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'ne3to3$any

2-'D C+ 9,*D'-

2-'D C+ 9,*D'-

$andatory= 'ne3to3'ne


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$andatory= ne3to3 ne

+'$'


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-ecursive

,$27'@,,supervises

is supervised by

-esolving $any3to3$any


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-elationships$any3to3many relationships should beavoided. e can resolve a many3to3manyrelationship by dividing it into two one3to3

many relationships.

-esolving $any3to3$any


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-elationships

! 7,! '-D,-! #*9. #+,$!

! 7,! '-D,-! #*9. #+,$!'-D,- #+,$!

xample ( - Diagram)


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,xample (,- Diagram)

! 7,! '-D,-!

#*9. #+,$!'-D,- #+,$!

C7,-?!C !+'$,-!


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I.

10

I.

10


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49959953 Data Flow Diagram