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
%.0
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
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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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,ntity3-elationship (,3-) $odeling?ey +erms
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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,ntity3-elationship (,3-) $odeling?ey +erms
#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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,ntity3-elationship (,3-) $odeling?ey +erms
-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.
$aximum Cardinality+he maximum number of instances of entity < thatmay be associated with each instance of entity
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I0
I.I0I.I0
*aming and Defining
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-elationships-elationship name is a verb phrase
void vague names&uidelines for defining relationships
Definition explains what action is being ta en and why it isimportant&ive examples to clarify the action'ptional participation should be explained,xplain reasons for any explicit maximum cardinality
*aming and Defining
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-elationships&uidelines for defining relationships
,xplain any restrictions on participation in therelationship,xplain extent of the history that is ept in therelationship,xplain whether an entity instance involved ina relationship instance can transferparticipation to another relationship instance
10.I"10.I"
ntity
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,ntity
M n entity is a business obAect thatrepresents a group= or category of data.N 1
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ttribute
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ttribute
M n attribute is a sub3group of informationwithin an entity.N 1
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$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 -+$,*+ !+ D,*+
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$any3to3$any
#*!+- C+'- !?#77
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'ne3to3$any
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$andatory= ne3to3 ne
+'$'
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-ecursive
,$27'@,,supervises
is supervised by
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-elationships$any3to3many relationships should beavoided. e can resolve a many3to3manyrelationship by dividing it into two one3to3
many relationships.
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-elationships
! 7,! '-D,-! #*9. #+,$!
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xample ( - Diagram)
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,xample (,- Diagram)
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10
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