Analyse Collective Cars

Table of Contents

1.        Introduction        

2.        Expert Systems Methods        

3.        Issues and Ethical Considerations        

4.        Features, Improvements and Future Extensions of the CCMS        

5.        Conclusion        

6.        Team Member Contributions        

7.        Group Reflection        

8.        Appendix        

1. Introduction

In this report we propose a database design model for the company ‘Collective Cars’. Collective Cars is a Sydney-based business that owns, manages and leases out cars from and to its member base. The company has 53 pickup zones throughout Sydney where cars can be dropped off or picked up by from members. As the business is expanding, management at Collective Cars are encountering database issues; the quality of data is decreasing with the increase in operational function. The system in question has been designed to set a database standard which ensures that Collective Cars can store, record, and increase its operational function without compromising data quality, integrity or potentially losing data.

The purpose of this report is to analyse Collective Cars as a business to scope out exactly what they need. Furthermore, this report aims to describe and outline the ‘Collective Cars Management System’ (CCMS) database for which they can implement. This report is structured to look at the CCMS database in question that has been designed. Following this, the report will have a deeper look at Collective Cars as a business then analyse any issues that may arise and improvements to the CCMS.

1. Expert Systems Methods

1. Relational Schema

As per the previously architected entity-relationship diagram, the following relational database schema has been proposed for the CCMS:[pic 1]

1. Querying the System and Database

Collective Cars have requested that a number of reports need to be generated which can query the database and return certain data/information. Considering the database is built in Oracle 11g as per the abstract, the queries have been generated in SQL and are as per below:

1. Member inquiry

This query lists all current members and their membership numbers for the pickup location “UNSW and Randwick” in the screenshot below:

[pic 2]

1. Payment Inquiry

This query will search for the member ‘Michael Rosemann’ and display his membership number and payments made in 2014.