Chapter 2 Conceptual Data Modeling

Transcription

1 Data Modelig ad Database Desig 2- hapter 2 oceptual Data Modelig hapter 2 Objectives After completig this chapter, the studet will uderstad: The fudametal terms (i.e., grammar) associated with the Etity-Relatioship Model Etity type Attribute Itegrity costraits as techical expressios of busiess rules Relatioship type Structural costraits of a relatioship type Base etity type versus weak etity type luster etity type Associative etity type Deletio rules/costraits ommo errors that occur durig the developmet of data models hapter 2 Overview This chapter itroduces the fudametal costructs ad rules for coceptual data modelig usig the etity-relatioship (ER) modelig grammar as the modelig tool. The basic uits of the ER model, that is, etity type, etity class, attribute, uique idetifier, ad relatioship type, are treated i detail. This is followed by exemplified descriptios of weak etity type, cluster etity type ad associative etity type. Fially, the role of deletio rules ad the specificatio of deletio costraits are discussed.

2 Data Modelig ad Database Desig 2-2 hapter 2 Key Terms Method Sematic modelig oceptual modelig script oceptual modelig grammar Object type Object Etity type Etity Object class Etity class Etity set Property Attribute Property value set Domai Data type Simple attribute omposite attribute I coceptual modelig, describes how to use the coceptual modelig grammar. The overall activity of attemptig to represet meaig. The product of coceptual data modelig. We just say coceptual modelig i the book. Defies the set of costructs ad rules for the coceptual modelig of a pheomeo. A amed collectio of properties that sufficietly describes a actual distict type of idetity i the real world. A actual occurrece of a object type (also referred to as a object istace or object occurrece). The coceptual represetatio of a object type. The occurrece of a etity type (also referred to as a etity istace or etity occurrece). A geeralizatio of differet related object types that have shared properties. A geeralizatio of differet related etity types that have shared attributes. A collectio of etities. A fudametal characteristic of a object type. A fudametal characteristic of a etity type (i.e., the coceptual represetatio of a property). The collectio of all possible values of a property. The collectio of all possible values of a attribute. A characteristic of a attribute; commo data types iclude umeric, alphabetic, alphaumeric, logical, ad date. A attribute that has a discrete factual value; a simple attribute is sometimes referred to as a atomic attribute. A attribute that ca be meaigfully subdivided ito smaller parts; a composite attribute is sometimes referred to as a molecular attribute.

3 Data Modelig ad Database Desig 2-3 Stored attribute Derived attribute Multi-valued attribute Sigle-valued attribute Madatory attribute Optioal attribute omplex attribute Sematic itegrity costrait Domai costrait Uiqueess costrait Uique idetifier Key attribute No-key attribute Relatioship type Degree of a relatioship type Biary relatioship type Terary relatioship type Quaterary relatioship type Recursive relatioship type Relatioship istace Relatioship set A attribute whose value is stored i the database. A attribute whose value ca be calculated from oe or more other attributes ad thus is ot stored i the database. A attribute that ca have more tha oe value for a particular etity. A attribute that ca have a sigle value for a particular etity. A attribute that must be assiged a value. A attribute that eed ot be assiged a value. A meaigful clusterig of composite ad/or multi-valued attributes. A busiess rule that caot be expressed explicitly or implicitly i the schema of a data model ad is carried forward through the data modelig tiers i textual form. A data itegrity costrait that establishes the rage of acceptable values for a attribute. A data itegrity costrait that requires etities of a etity type be uiquely idetifiable. A atomic or composite attribute whose values are distict for each etity i the etity set. A attribute that is a costituet part of a uique idetifier. A attribute that is ot a costituet part of a uique idetifier. A meaigful associatio amog etity types. The umber of etity types participatig i the relatioship type. A relatioship type i which two etity types are ivolved. A relatioship type i which three etity types are ivolved. A relatioship type i which four etity types are ivolved. A relatioship type i which oe etity type is ivolved. A occurrece of a relatioship type. The set of all relatioship istaces.

4 Data Modelig ad Database Desig 2-4 Istace diagram Role ame Structural costraits of a relatioship type ardiality costrait Participatio costrait Total (Madatory) participatio Partial (Optioal) participatio Existece depedecy Weak etity type Base etity type Partial key Discrimiator Idetifyig relatioship Deletio costrait A diagrammatic represetatio of the relatioship amog the istaces of the participatig etity types. A term used to describe the participatio of a etity type i a relatioship type. The data itegrity costraits pertaiig to relatioship types specified i a ER diagram. A data itegrity costrait that specifies the maximum umber of istaces of a etity type that relate to a sigle istace of a associated etity type through a particular relatioship type. A data itegrity costrait for a etity type i a biary relatioship based o whether, i order to exist, a etity of that etity type eeds to be related to a etity of the other etity type through this relatioship type. Occurs whe every etity must participate i at least oe occurrece of a relatioship type. Occurs whe every etity is ot required to participate i at least oe occurrece of a relatioship type. Occurs whe total participatio of a etity type i a relatioship type exists. A etity type that does ot have its ow uique idetifier. A etity type where the etities have idepedet existece. A attribute, atomic or composite, i a weak etity type which, i cojuctio with a uique idetifier of the paret etity type i the idetifyig relatioship type, uiquely idetifies a weak etity. A term sometimes used i place of the term partial key. A relatioship betwee a base etity type ad a weak etity type. I the cotext of the deletio of a etity from the paret etity type, requires specific actio either i the paret etity set or i the child etity set i order to maitai cosistecy of the relatioships i

5 Data Modelig ad Database Desig 2-5 Restrict rule ascade rule Set ull rule Set default rule luster etity type the database. A deletio rule where the deletio of a paret etity i a relatioship is restricted if all child etities related to the paret i the relatioship should ot be deleted. A deletio rule where the deletio of a paret etity i a relatioship also causes all child etities related to the paret i the relatioship to be deleted. A deletio rule where the deletio of a paret etity i a relatioship allows all child etities related to the paret i the relatioship to be retaied but o loger refereced to the paret. A deletio rule where the deletio of a paret etity i a relatioship allows all child etities related to the paret i the relatioship to be retaied but o loger refereced to the paret but istead refereced to a predefied default paret. A etity type emergig as a result of a groupig operatio o a collectio of etity types ad relatioship(s) amog them; idicated i a etity-relatioship diagram by a dotted rectagle. hapter 2 Solutios. What is the differece betwee the coceptual world ad the real world? Is it possible for a coceptual model to represet reality i total? Why or why ot? Aswer. The real world cosists of (a) tagible objects of a object type ad (b) itagible objects of a object type. The coceptual world cosists of represetatios, i the form of etity types, of these real world tagible ad itagible objects. It is ot possible for a coceptual model to represet the real world, but oly to represet the modeler s view of the real world (which we call i hapter the Uiverse of Iterest or portio of reality). 2. Use examples to distiguish betwee: a. A object type ad a etity type A object type is a amed collectio of properties that sufficietly describes a actual distict type of idetity. A object type ca be tagible (e.g., a vehicle) or itagible (e.g., project). A etity type is a coceptual represetatio of a object type (e.g., a drawig of a vehicle). b. A object ad a etity A object is a actual occurrece of a object type (e.g., a actual vehicle). A etity is a occurrece of a etity type (i.e., the represetatio of a vehicle i a VEHILE data set).

6 Data Modelig ad Database Desig 2-6 c. A property ad a attribute A property is a characteristic of a object type, whereas a attribute is a characteristic of a etity type. For example, the measured weight of a perso would be termed a property, whereas the weight of the same perso as recorded as a umeric value i a database would be termed a attribute. d. A etity ad a etity istace A etity ad a etity istace are oe i the same. Both refer to a occurrece of a etity type. For example, the record for Aa Li i a STUDENT data set would be termed a etity or etity istace. e. A associatio ad a relatioship Associatios exist i the real world betwee object types (e.g., a specific faculty member advises a specific group of studets). I the coceptual world, such associatios are referred to as relatioships betwee etity types. f. A object class ad a etity class A object class is a geeralizatio of differet related object types that have shared properties. For example, the object types basketball player, baseball player, ad football player ca be said to belog to the object class athlete. A etity class is a geeralizatio of differet related etity types that have shared attributes.

7 Data Modelig ad Database Desig Describe various data types associated with attributes. Aswer. A variety of data types ca be associated with attributes. Those metioed i hapter 2 follow. A umeric data type is used whe a attribute s value ca cosist of positive ad egative umbers ad is ofte used i arithmetic operatios. A alphabetic data type permits a attribute to cosist of oly letters ad spaces, whereas a alphaumeric data type allows the value of a attribute to cosist of text, umbers, ad certai special characters. A logical data type is associated with a attribute whose value ca be either true or false (e.g., the attribute taxable). A date data type is used for storig a date (e.g., date hired or date of birth). 4. What is the differece betwee a stored attribute ad a derived attribute? Aswer. A stored attribute is oe whose value is stored i the database. O the other had, a derived attribute is oe whose value ca be calculated or derived from the values of other attributes. At the physical level, typically derived attributes are ot stored i a database. 5. What would be the domai of the attribute outy_ame i the state of Texas? Aswer. The domai of the attribute outy_ame would be the set of all couty ames i the state of Texas. 6. Distiguish betwee a simple attribute, a sigle-valued attribute, a composite attribute, a multi-valued attribute, ad a complex attribute. Develop a example similar to Figure 2.3 that illustrates the differece betwee each type of attribute. Aswer. A attribute that has a discrete factual value ad caot be meaigfully subdivided is called a atomic or simple attribute. A composite attribute, o the other had, ca be meaigfully subdivided ito smaller subparts with idepedet meaig. A sigle-valued attribute has a sigle value for a particular etity, whereas a multi-valued attribute ca have more tha oe value for a particular etity. Both simple ad composite attributes ca be sigle-valued or multi-valued. A complex attribute is a cluster of composite ad multi-valued attributes. 7. What is a uique idetifier of a etity type? Is it possible for there to be more tha oe uique idetifier for a etity type? Aswer. A attribute, atomic (i.e., simple) or composite, whose values are distict for each etity i the etity set, is the uique idetifier of the etity type. Yes, there ca be more tha oe uique idetifier for a etity type. 8. What is the differece betwee a key attribute ad a o-key attribute? Aswer. A key attribute is ay attribute that is part of a uique idetifier. A o-key attribute is oe that is ot a costituet part of ay uique idetifier.

8 Data Modelig ad Database Desig osider the EMPLOYEE etity type give below. a. List all key ad o-key attributes. Key attributes Fame, Miit, Lame, Name_tag. The attributes Fame, Miit, Lame, ad Name_tag are key attributes because they are costituet parts of the composite idetifier Name. No-key attributes Address, Salary, Geder, Date_hired, No_of_depedets; these five simple attributes have othig to do with ay idetifier. b. What is (are) the uique idetifier(s)? Emp# ad Name; i other words, we have a uique idetifier that is a simple (atomic) attribute ad aother that is a composite attribute. c. Which attribute(s) is (are) derived attributes? No_of_depedets. Note: We have see studets idicate that a perso s ame as a combiatio of his or her first ame, middle iitial, last ame, ad ame tag, costitutes a derived attribute. While perhaps a reasoable thig to do, this is ot correct. d. Usig the figure i Exercise 9 as a guide, develop sample data for four employees that illustrate the ature of the various madatory ad optioal attributes i the EMPLOYEE etity. Be sure to illustrate the various ways the Name attribute might appear. 00 Joh Doe 23 Ay Male /23/0 Emp# Name_Fame Name_Miit Name_Lame Name_tag Address Salary Geder Date_hired Teure 002 Fred J Flistoe 32 There 39,000 Male 2/26/02 2 Emp# Name_Fame Name_Miit Name_Lame Name_tag Address Salary Geder Date_hired Teure 003 Barey Rubble BQT 322 There Male 3//0 Emp# Name_Fame Name_Miit Name_Lame Name_tag Address Salary Geder Date_hired Teure 004 Lisa M Presley LMP 24 Pea 88,000 Female 4/2/02 Emp# Name_Fame Name_Miit Name_Lame Name_tag Address Salary Geder Date_hired Teure Note how this example shows how the Name attribute might appear four differet ways: oe time with just the first ame ad last ame; oe time with the first ame, middle iitial, last ame; a third time with a first ame, last ame, ad ame tag; ad a fourth time with a first ame, middle iitial, last ame, ad ame tag. Sice first ame ad last ame are required attributes, they appear for each employee. Middle iitial appears twice: oce with a ame tag ad oce without a ame tag. Likewise, middle iitial does ot appear two times, oce with a ame tag ad oce without a ame tag. 0. Discuss how to distiguish betwee a etity type ad a attribute. Aswer. A etity type correspods to a aggregatio of attributes.

9 Data Modelig ad Database Desig 2-9. Give a example of three etity types ad accompayig attributes that might be associated with a database for a car retal agecy. Aswer. VEHILE (VehicleID, LicesePlate#, Make, Model, Year, Mileage, ) RENTER (Licese#, Name, Address, ity, State, Zipcode, Isurace, etc.) VEHILE_RENTAL (VehicleID, Licese#, Dateout, Datei, Mileageout, Mileagei) 2. What is a relatioship type? How does a relatioship type differ from a relatioship istace? Aswer. A relatioship type is a meaigful associatio amog etity types. A relatioship istace is a occurrece of a relatioship type. 3. What is meat by the degree of a relatioship? Aswer. The degree of a relatioship type is defied as the umber of etity types participatig i that relatioship type. 4. What is the value of usig role ames to describe the participatio of a etity type i a relatioship type? Aswer. Role ames ca be used to clarify the ature of the participatio of each etity type ivolved i a relatioship type. They ca be particularly helpful i clarifyig the ature of the structural costraits i a recursive relatioship. 5. What is the differece betwee a biary relatioship that exhibits a : cardiality costrait ad a biary relatioship that exhibits a : cardiality costrait? Aswer. I a biary relatioship that exhibits a : cardiality ratio, each occurrece of etity type E is associated with at most oe occurrece of etity type E2 ad vice versa. I a biary relatioship that exhibits a : relatioship, each occurrece of etity type E is associated with, at oce, occurreces of etity type E2, while each occurrece of etity type E2 is associated with, at most, oe occurrece of etity type E.

10 Data Modelig ad Database Desig Describe how Married_to ca be modeled as a recursive relatioship. Aswer. Married_to ca be modeled as a recursive relatioship type if you thik of it i terms of a PERSON etity type (e.g., Perso ca be married to at most oe other perso, Perso 2 ca be married to at most oe other perso either Perso or Perso 3 or Perso, etc.). The followig is a example of what a ER diagram ad accompayig istace diagram might look like. PERSON PERSON p h w Married_to r Husbad Wife p2 Married_to p3 p4 w h r2 p5 p6 Istace Diagram 7. reate a example of a recursive relatioship with a m: cardiality costrait. Aswer. A possible example is a doctor treatig other doctors as his/her patiets ad at the same time, a doctor beig treated as a patiet by other doctors. DOTOR Doctor_of Patiet_of Treatmet m 8. Distiguish betwee a participatio costrait ad miimum cardiality. Aswer. The participatio costrait is also referred to as miimum cardiality. 9. Why ca total participatio of a etity type i a relatioship type also be referred to as existece depedecy of that etity type i that relatioship type? Aswer. Total participatio occurs if i order to exist, a etity type must participate i the relatioship. Thus, total participatio of a etity type i a relatioship type ca be termed existece depedecy of that etity type i that relatioship type.

11 Data Modelig ad Database Desig How do cardiality costraits ad participatio costraits relate to the otios of total ad partial participatio? Aswer. A cardiality costrait has othig to do with the otios of total ad partial participatio. Partial participatio occurs if a etity type ca exist without participatio i a relatioship, whereas total participatio requires that a etity type must participate i the relatioship i order to exist. 2. Discuss the differece betwee existece depedecy ad idetificatio depedecy. Aswer. Total participatio of a etity type i a relatioship type is defied as existece depedecy. Idetificatio depedecy is existece depedecy where a weak etity type is always depedet o the uique idetifier of its idetifyig paret for its uique idetificatio. 22. Give a example of a relatioship type betwee two etity types where a attribute ca be assiged to the relatioship type istead of to oe of the two etity types. Aswer. A good example ivolves the situatio i Exercises 26 ad 27 below, where the attribute commissio is defied as the commissio received by a isurace aget for the sale of a policy to a cliet. Aother example could ivolve a relatioship such as the followig: Amout DONOR Doates_to m HARITABLE_ ORGANIZATION 23. What is the differece betwee a base etity type ad a weak etity type? Aswer. A base etity type is oe where each etity has idepedet existece (i.e., each etity is uique). A weak etity type is oe where each etity does ot have idepedet existece (duplicate etities may exist). A weak etity type is show to make it clear that the etity type does ot have a uique idetifier. 24. Defie the term partial key. Aswer. A partial key is a idetifier of a weak etity type. By itself, it is ot a uique idetifier, but whe combied with the uique idetifier of the idetifyig paret of the weak etity type, it uiquely idetifies weak etities.

12 Data Modelig ad Database Desig This is a arrative about a small uiversity i Kodai, A. There are several colleges i the uiversity. Each college has a ame, locatio, ad size. A college offers may courses over four college terms or quarters Fall, Witer, Sprig, ad Summer durig which oe or more of these courses are offered. ourse#, Name, ad credit hours describe a course. No two courses i ay college have the same ourse#; likewise, o two courses have the same Name. Terms are idetified by year ad quarter, ad cotai umbers. ourses are offered durig every term. The college also has several istructors. Istructors teach; that is why they are called istructors. Ofte, ot all istructors are scheduled to teach durig all terms; but every term has some istructors teachig. Also, the same course is ever taught by more tha oe istructor i a specific term. Further, istructors are capable of teachig a variety of courses offered by the college. Istructors have a uique employee ID ad their ame, qualificatio, ad experiece are also recorded. a. List the busiess rules explicitly stated ad implicitly idicated i the arrative. b. Study the arrative carefully ad idetify the missig iformatio required for developig a sematically complete coceptual data model. a. Extracted busiess rules: There are four quarters; specifically, they are Fall, Witer, Sprig, ad Summer. A college offers may courses. At least 23 courses are offered durig every quarter. A college has several istructors. A istructor eed ot teach i a give quarter. A istructor is capable of teachig a variety of courses offered by the college. Iferred busiess rules: A istructor must teach i some quarter. A istructor must be capable of teachig at least oe course that the college offers. b. Ambiguities that require clarificatio: Is a particular course offered i more tha oe quarter? Are there courses that are just i the books but are ever offered? a a istructor teach for more tha oe college i the uiversity?

13 Data Modelig ad Database Desig The istace diagram show below illustrates the relatioship betwee Sulliva Isurace Agecy s agets ad cliets. Usig this istace diagram, write the arrative that describes the relatioship betwee agets ad cliets. Your arrative should iclude a descriptio of both the cardiality ratio ad participatio costraits implied i the istace diagram. I additio, draw the ER diagram that fully describes the relatioship betwee the compay s agets ad cliets. Aswer. Sulliva Isurace ompay agets sell isurace policies to cliets. More experieced agets ofte sell separate policies to may differet cliets, while ewer agets may sell oe. Likewise, ot all cliets have purchased a policy from a aget, whereas some cliets have purchased a policy from more tha oe aget. m LIENT Policy AGENT

14 Data Modelig ad Database Desig Revise the ER diagram draw i the previous exercise to iclude the followig madatory attributes: LIENT ID umber, ame, address (city, state, zip), phoe umber(s), birthdate; AGENT aget umber, ame, phoe umber, area; ad commissio received by a aget for sellig a Policy to a cliet. Aswer. O this exercise, what we were really lookig for was how the studet hadled the commissio attribute. Note that commissio is defied as commissio received by a aget for sellig a Policy to a cliet. As a product of the relatioship betwee a LIENT ad a AGENT, commissio should be show as a attribute of the relatioship type Policy. Sice the cardiality ratio is m:, it caot be show as a attribute of aget. However, had commissio bee defied as simply a aual percetage of sales that a aget receives for a give period based o performace, the it would be a attribute of AGENT. ity State Zip ID Number Name Address Phoe umber m LIENT Birthdate ommissio Policy Aget umber AGENT Name Area Phoe umber

15 Data Modelig ad Database Desig Use the istace diagram depictig the terary relatioship Orders show o the ext page to aswer the followig questios. a. Which customers order pes from the Galvesto warehouse? No customers order pes from the Galvesto warehouse, as the Galvesto warehouse does ot supply pes. b. Which items are ordered by customers from both warehouses? Pecils are ordered from both warehouses. c. Which warehouse fills oe or more orders of items from both customers? The Galvesto warehouse takes oe or more orders from both customers. d. Describe orders filled from both warehouses. This questio is poorly worded ad may geerate several differet aswers. What we were lookig for related to order r2, which ivolves Ives orderig pecils from both the Galvesto ad harlotte warehouses. Some studets may provide a descriptio of all orders, which i essece cotais what we were lookig for alog with a descriptio of orders that techically we were ot lookig for. e. What chages must be made to the istace diagram for order r to ivolve both pecils ad pes? Just as we have two warehouses goig to order r2, this questio ecessitates two items leadig ito order r. This was aother questio that perhaps could be worded better, as it ca geerate iterestig aswers to a slightly differet questio. 29. The followig two ER diagrams cotai both a cardiality ratio costrait ad a participatio costrait. a. I the first ER diagram, is the istace diagram o the right cosistet with the ER diagram o the left? Why or why ot? Sells SALESPERSON SALESPERSON SALES r VEHILE v Sales s r2 v2 s2 r3 v3 Sold_by VEHILE s3 r4 v4 r5 v5 Istace Diagram I the first ER diagram, the istace diagram o the right is ot cosistet with the ER diagram o the left. The ER diagram specifies total participatio of VEHILE i relatioship Sales. But the, v3 i the istace diagram does ot participate i the relatioship.

16 Data Modelig ad Database Desig 2-6 b. I the secod ER diagram, is the istace diagram o the right cosistet with the ER diagram o the left? Why or why ot? Sells Sales Sold_by SALESPERSON VEHILE SALESPERSON s s2 s3 SALES r r2 r3 r4 VEHILE v v2 v3 v4 v5 Istace Diagram I the secod ER diagram, the istace diagram o the right is ot cosistet with the ER diagram o the left. The ER diagram specifies total participatio of SALESPERSON i relatioship Sales. But the, s2 i the istace diagram does ot participate i the relatioship. 30. Suppose you wat to show that a perso ca have multiple degrees. Would each of the followig two ER diagrams get the job doe? Why or why ot? What is the differece? Birthdate SSN Last PERSON Phoe Educatio BBA-MIS MBA-Acctg Birthdate SSN Last PERSON Phoe Educatio Name Name First Ph.D-Fiace First The ER diagram o the left permits specificatio of a maximum of three degrees - i fact, oly three specific degrees. The ER diagram o the right, however, is more flexible i that it permits specificatio of multiple degrees of ay kid icludig o degrees.

17 Data Modelig ad Database Desig Adams, Ives, ad Scott Icorporated is a agecy that specializes i represetig cliets i the fields of sports ad etertaimet. Give the ature of the busiess, some employees are give a compay car to drive, ad each compay car must be assiged to a employee. Each employee has a uique employee umber, plus a address ad set of certificatios. Not all employees have eared oe or more certificatios. ompay cars are idetified by their vehicle id, ad also cotai a licese plate umber, make, model, ad year. Employees represet cliets. Not all employees represet cliets, while some employees represet may cliets. Each cliet is represeted by oe ad oly oe employee. Sometimes cliets refer oe aother to use Adams, Ives, ad Scott to represet them. A give cliet ca refer oe or more other cliets. A cliet may or may ot have bee referred to Adams, Ives, ad Scott by aother cliet, but a cliet may be referred by oly oe other cliet. Each cliet is assiged a uique cliet umber. Additioal attributes recorded for each cliet are ame, address, ad date of birth. Draw a ER diagram that shows the etity types ad relatioship types for Adams, Ives, ad Scott. While you must ame each relatioship type ad defie its structural costraits, it is ot ecessary that you supply role ames. Vehicle_ID Licese# Make Address Emp# ertificatio Model VEHILE Vehicle_ assigmet EMPLOYEE Year Represets lieto Name Address Birthdate LIENT Refers Referred_by Referred_by

18 Data Modelig ad Database Desig 2-8 ommets: It is possible that some studets may model ERTIFIATION as a etity type istead of a multi-valued attribute ad the establish a relatioship with a m: cardiality ratio betwee EMPLOYEE ad ERTIFIATION. This was a good alterative, although i doig so, it is ecessary to ivet a attribute for the ERTIFIATION etity type sice oe was give i the problem. 32. Draw the ER diagram for the two istace diagrams depicted here. NEW_ASSET AIRFORE_BASE A A2 A3 A4 A5 Scheduled_for r r2 r3 r4 r5 r6 S S2 S3 S4 S5 S6 S7 S8 S9 Assiged_to r7 r8 r9 r0 r NAVAL BASE N N2 N3 S0 S NAVAL_BASE Assiged_to NEW_ASSET Scheduled_for AIRFORE_BASE

19 Data Modelig ad Database Desig 2-9 PROPERTY P P2 REALTOR L L2 L3 L4 L5 Sold_by r r2 r3 r4 r5 r6 P3 P4 P5 P6 P7 P8 P9 Bought_by r7 r8 r9 r0 USTOMER 2 3 P0 P USTOMER Assiged_to PROPERTY Scheduled_for REALTOR 33. This vigette is a small excerpt from a comprehesive case about a cliic. Various physicias ad surgeos workig for a cliic are o a aual salary [o]. These doctors are idetified by their respective employee umbers. The other descriptors of a doctor are: ame, geder, address, ad phoe. Each physicia s specialty ad rak [o] are captured; each surgeo s, specialty ad skill are also captured; a surgeo may have oe or more skills. Every physicia serves as a primary care physicia for at least seve patiets; however, o more tha 20 patiets are allotted to a physicia. Every patiet is assiged oe physicia for primary care. Some patiets eed surgeries; others do t. Surgeos perform surgeries for the patiets i the cliic. Some do a lot of surgeries; others do just a few. The date ad operatio theater [o] for each surgery eeds to be recorded, too. Removal of a surgeo from the cliic database is prohibited if that

20 Data Modelig ad Database Desig 2-20 surgeo is scheduled to perform ay surgery. However, if a patiet chooses to pull out of the surgery schedule, all surgeries scheduled for that patiet are cacelled. Data for patiets iclude: patiet umber (the uique idetifier of a patiet), ame, geder, date of birth, blood type, cholesterol (cosistig of HDL, LDL, ad triglyceride), blood sugar, ad the code ad ame of allergies, if ay. Physicias may prescribe medicatios to patiets; thus, it is ecessary to capture which physicia(s) prescribe(s)s what medicatio(s) to which patiet(s) alog with dosage ad frequecy. I additio, o two physicias ca prescribe the same medicatio to the same patiet. If a physicia leaves the cliic, all prescriptios writte by that physicia should also be removed because this iformatio is retaied i the archives. A patiet may be takig several medicatios, ad a particular medicatio may be take by several patiets. Despite its list price, a medicatio s cost varies from patiet to patiet, perhaps because of the differece i isurace coverage. The cost of a medicatio for a patiet eeds to be captured. A medicatio may iteract with several other medicatios. Whe a medicatio is removed from the system, its iteractio with other medicatios, if ay, should be voided. Whe a patiet leaves the cliic, all the medicatio records for that patiet are removed from the system. Medicatios are idetified by either their uique medicatio codes or by their uique ames. Other attributes of a medicatio are its classificatio, list price, ad maufacturer [o]. For every medicatio, either the medicatio code or the medicatio ame must be preset ot ecessarily both. Note: [o] idicates optioality of value for the attribute. Develop a ER model for this sceario. Speciality Rak Emp_umb Address Name Emp_umb Salary Geder Role PERSONNEL R R Is_also Surg_sch PHYSIIAN PP* Theatre Surg_date m R 20 Dosage Iteracts Writes Frequecy R lassificatio MEDIATION PRESRIPTION N Takes List_price Maufacturer Med_code Name Belogs_to m ode Allergy PATIENT Blood_type ost SURGEON Speciality Emp_umb Skill Blood_sugar Alg_ame Patiet# Name HDL holesterol Birthdate LDL Triglyceride Geder Deletio costraits eclosed i a box (highlighted i red) reflect erroeous/coflictig deletio (busiess) rules. A few differet ways of correctio are possible. Oce such correctio is show i the ext ER diagram

21 Data Modelig ad Database Desig 2-2 Speciality Rak Emp_umb Address Name Emp_umb Salary Geder Role PERSONNEL R R Is_also Surg_sch PHYSIIAN PP* Theatre Surg_date m R 20 Dosage Iteracts Writes Frequecy PRESRIPTION N lassificatio MEDIATION R List_price Takes Med_code Maufacturer Name Belogs_to m R ode Allergy PATIENT Blood_type ost SURGEON Blood_sugar Alg_ame Patiet# Speciality Skill Emp_umb HDL LDL Name holesterol Birthdate Triglyceride Geder