SBM4201 System Analysis and Design: ER Diagram for NSW Car Rental
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AI Summary
This document provides a system analysis and design solution for the NSW car rental company database, focusing on the creation of an Entity-Relationship (ER) diagram. It identifies key entities such as Staffs, Addresses, Customer, Rentals, Reservation, Vehicle, and Vehicle Category, along with their respective attributes. The ER diagram visually represents the relationships between these entities. Assumptions are made to clarify certain aspects of the case study, such as the multi-valued nature of addresses and the categorization of vehicles. The document includes a logical model defining primary and foreign keys for each entity and concludes with a bibliography of cited sources. Desklib offers this and other solved assignments to aid students in their studies.

Running head: SYSTEM ANALYSIS AND DESIGN
System Analysis and Design
Name of the Student:
Name of the University:
Author Note
System Analysis and Design
Name of the Student:
Name of the University:
Author Note
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1
SYSTEM ANALYSIS AND DESIGN
List of Entities and Attributes
The identified list of entities is provided below:
Staffs
Addresses
Customer
Rentals
Reservation
Vehicle
Vehicle Category
The identified list of attributes for each of the entities are provided below:
Staffs: StaffNumber, FName, LName, HomeAddress, Gender, DateOfBirth,
OfficeNumber, OfficePhoneNumber
Addresses: HomeAddress, StreetNumber, Suburd, Post-Code, City, State
Customer: CustomerNumber, FirstName, LastName, HomeAddress, Gender,
DateOfBirth, TelephoneNumber, DriverLicenseNumber
Rentals: RentID, RegistrationNumber, CustomerNumber, Borrow_Date, Return_Date,
TotalCost, StaffNumber, VehicleCondition
Reservation: ReservationID, RegistrationNumber, CustomerNumber,
ReservationPeriod, TotalCost, StaffNumber, VehicleCondition
Vehicle: RegistrationNumber, CategoryName, Make, Model, Colour,
Rental_Price/Day
Vehicle Category: CategoryName, Rental_Charges, NumberOSeats
After the identification of the list of entities and attributes the logical model can be
created as defined below:
SYSTEM ANALYSIS AND DESIGN
List of Entities and Attributes
The identified list of entities is provided below:
Staffs
Addresses
Customer
Rentals
Reservation
Vehicle
Vehicle Category
The identified list of attributes for each of the entities are provided below:
Staffs: StaffNumber, FName, LName, HomeAddress, Gender, DateOfBirth,
OfficeNumber, OfficePhoneNumber
Addresses: HomeAddress, StreetNumber, Suburd, Post-Code, City, State
Customer: CustomerNumber, FirstName, LastName, HomeAddress, Gender,
DateOfBirth, TelephoneNumber, DriverLicenseNumber
Rentals: RentID, RegistrationNumber, CustomerNumber, Borrow_Date, Return_Date,
TotalCost, StaffNumber, VehicleCondition
Reservation: ReservationID, RegistrationNumber, CustomerNumber,
ReservationPeriod, TotalCost, StaffNumber, VehicleCondition
Vehicle: RegistrationNumber, CategoryName, Make, Model, Colour,
Rental_Price/Day
Vehicle Category: CategoryName, Rental_Charges, NumberOSeats
After the identification of the list of entities and attributes the logical model can be
created as defined below:

2
SYSTEM ANALYSIS AND DESIGN
Staffs (StaffNumber (primary key), FName, LName, HomeAddress (foreign key), Gender,
DateOfBirth, OfficeNumber, OfficePhoneNumber)
Addresses: HomeAddress (primary key), StreetNumber, Suburd, Post-Code, City, State
Customer: CustomerNumber (primary key), FirstName, LastName, HomeAddress (foreign
key), Gender, DateOfBirth, TelephoneNumber, DriverLicenseNumber
Rentals: RentID (primary key), RegistrationNumber (foreign key), CustomerNumber (foreign
key), Borrow_Date, Return_Date, TotalCost, StaffNumber, VehicleCondition
Reservation: ReservationID (primary key), RegistrationNumber (foreign key),
CustomerNumber (foreign key), ReservationPeriod, TotalCost, StaffNumber,
VehicleCondition
Vehicle: RegistrationNumber (primary key), CategoryName (foreign key), Make, Model,
Colour, Rental_Price/Day
Vehicle Category: CategoryName (primary key), Rental_Charges, NumberOSeats
SYSTEM ANALYSIS AND DESIGN
Staffs (StaffNumber (primary key), FName, LName, HomeAddress (foreign key), Gender,
DateOfBirth, OfficeNumber, OfficePhoneNumber)
Addresses: HomeAddress (primary key), StreetNumber, Suburd, Post-Code, City, State
Customer: CustomerNumber (primary key), FirstName, LastName, HomeAddress (foreign
key), Gender, DateOfBirth, TelephoneNumber, DriverLicenseNumber
Rentals: RentID (primary key), RegistrationNumber (foreign key), CustomerNumber (foreign
key), Borrow_Date, Return_Date, TotalCost, StaffNumber, VehicleCondition
Reservation: ReservationID (primary key), RegistrationNumber (foreign key),
CustomerNumber (foreign key), ReservationPeriod, TotalCost, StaffNumber,
VehicleCondition
Vehicle: RegistrationNumber (primary key), CategoryName (foreign key), Make, Model,
Colour, Rental_Price/Day
Vehicle Category: CategoryName (primary key), Rental_Charges, NumberOSeats
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SYSTEM ANALYSIS AND DESIGN
ER Diagram
Figure 1: ER Diagram of NSW Car Rental System
Source: (Created by Author)
Assumptions and Justification of the ER Diagram
For the creation of the ER Diagram provided above it is to be noted that majority of
the information has been taken from the case study. However, some additional assumptions
were required before the ER Diagram could be implemented for the formulation of a clear
idea.
SYSTEM ANALYSIS AND DESIGN
ER Diagram
Figure 1: ER Diagram of NSW Car Rental System
Source: (Created by Author)
Assumptions and Justification of the ER Diagram
For the creation of the ER Diagram provided above it is to be noted that majority of
the information has been taken from the case study. However, some additional assumptions
were required before the ER Diagram could be implemented for the formulation of a clear
idea.
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SYSTEM ANALYSIS AND DESIGN
It is to be noted that the case study has defined the home addresses of the customers
and the staffs of the organization as a single attribute but it is to be noted that the attribute is
multi valued one and for denoting the multivalued an additional entity has been assumed and
all the sub attributes of the main attribute has been added as the main attributes in the Home
Address entity.
In addition to this, it is to be noted that the Vehicles are identified by their unique
registration number, however no information about the categorization of the vehicles has
been provided and hence, it has been assumed that there would be some categories and hence
an entity named vehicle category has been added to the Diagram.
It has also been assumed that the Rentals of the organization would be identified by
some unique fields and the filed is denoted by RentID in the rent entity.
SYSTEM ANALYSIS AND DESIGN
It is to be noted that the case study has defined the home addresses of the customers
and the staffs of the organization as a single attribute but it is to be noted that the attribute is
multi valued one and for denoting the multivalued an additional entity has been assumed and
all the sub attributes of the main attribute has been added as the main attributes in the Home
Address entity.
In addition to this, it is to be noted that the Vehicles are identified by their unique
registration number, however no information about the categorization of the vehicles has
been provided and hence, it has been assumed that there would be some categories and hence
an entity named vehicle category has been added to the Diagram.
It has also been assumed that the Rentals of the organization would be identified by
some unique fields and the filed is denoted by RentID in the rent entity.

5
SYSTEM ANALYSIS AND DESIGN
Bibliography
Bull, E.R., Dombrowski, S.U., McCleary, N. and Johnston, M., 2014. Are interventions for
low-income groups effective in changing healthy eating, physical activity and smoking
behaviours? A systematic review and meta-analysis. BMJ open, 4(11), p.e006046.
Elias-Miró, J., Grojean, C., Gupta, R.S. and Marzocca, D., 2014. Scaling and tuning of EW
and Higgs observables. Journal of High Energy Physics, 2014(5), p.19.
Jung, T., Jo, H.L., Nam, S.H., Yoo, B., Cho, Y., Kim, J., Kim, H.M., Hyeon, T., Suh, Y.D.,
Lee, H. and Lee, K.T., 2015. The preferred upconversion pathway for the red emission of
lanthanide-doped upconverting nanoparticles, NaYF 4: Yb 3+, Er 3+. Physical Chemistry
Chemical Physics, 17(20), pp.13201-13205.
Kern, E.R. and Lardinois, S.M., International Business Machines Corp, 2014. Sharing
computer data among computers. U.S. Patent 8,868,628.
SYSTEM ANALYSIS AND DESIGN
Bibliography
Bull, E.R., Dombrowski, S.U., McCleary, N. and Johnston, M., 2014. Are interventions for
low-income groups effective in changing healthy eating, physical activity and smoking
behaviours? A systematic review and meta-analysis. BMJ open, 4(11), p.e006046.
Elias-Miró, J., Grojean, C., Gupta, R.S. and Marzocca, D., 2014. Scaling and tuning of EW
and Higgs observables. Journal of High Energy Physics, 2014(5), p.19.
Jung, T., Jo, H.L., Nam, S.H., Yoo, B., Cho, Y., Kim, J., Kim, H.M., Hyeon, T., Suh, Y.D.,
Lee, H. and Lee, K.T., 2015. The preferred upconversion pathway for the red emission of
lanthanide-doped upconverting nanoparticles, NaYF 4: Yb 3+, Er 3+. Physical Chemistry
Chemical Physics, 17(20), pp.13201-13205.
Kern, E.R. and Lardinois, S.M., International Business Machines Corp, 2014. Sharing
computer data among computers. U.S. Patent 8,868,628.
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