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MIS602 Assign1 Page 1 of 3

ASSESSMENT BRIEF

Subject Code and Name MIS602 Data Modelling & Database Design

Assessment One – Peer Assessment of File-based Database Design

Individual/Group Individual

Length See below for details

Learning Outcomes B

Submission Thursday 11:59 PM AEST/AEDT of Module 2 (week 4)

Sunday 11:59 PM AEST/AEDT of Module 2 (week 4)

Weighting 25%

Total Marks 25 marks

Context:

The MIS602 Data Modelling & Database Design subject is designed for you to progressively add to
your understanding of data and database management and its relevance with in business context. It

also introduces you to some of the key features of database management system and designing

database systems that will feature in later modules of this topic. In order for you to do well in this

subject, it is imperative that you undertake all of the learning activities in the modules. The learning

activities are presented as a way of scaffolding your learning so that you can attempt the building

blocks of the assessments and be in a safe environment to fail and to learn from them. Therefore,

doing your learning activities and seeking feedback from them from peers and from the learning

facilitator is the single best way of preparing for doing well in this assessment.

Instructions:

There is an imperative requirement in this assessment; you must submit different versions of the
files by Thursday of week 4 at midnight (Sydney time). The files should ideally be of excel format.
The data in the files should be composed based on the following scenario:

Torrens University Australia (TUA) is interested in a new Student record management
system. This system needs a database to manage students enrolled, courses students
enrolled in and staff facilitating the course. You will need to store and manage the data for
the enrolled students, courses and the staff assigned to the courses. The system is intended
to be built in-house. The university has a very strong information systems suite of programs
and the students of that program are showing great insight and promise. It has signalled its
intention to seek input from those students in a consulting arrangement.

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The system should allow the staff to add, update and delete the records of students, staff
allocated to course and courses. In addition, University staff should be able to see the list of
students enrolled in a particular course facilitated by a particular learning facilitator.

Based on this scenario, you should identify key data objects and their attributes and define them as
columns in the spreadsheet. Create multiple versions of the spreadsheet file as per below
instruction:

• Version 1 (V1.0) with all possible database objects and attributes and create 30 rows of data.
• Version 2 (V1.1) of the file should update last 2 records and add 5 additional records
• Version 3 (V1.2) of the file should add 2 new attributes
• Version 4 (V1.3) of the file should remove 5 existing attribute and add 5 more rows of data

When you are finished this, combine the four versions of the Excel database solution with a
document that in more than 1000 words, describing your experience. On the morning following
submission, the learning facilitator will allocate you another student’s spreadsheets and summary
document to assess. It is then your turn to assess another student’s work. You will have three days
to assess the other student’s work and to upload your response to Blackboard.

In no more than 500 words, provide a critique of that student’s work to them. You can choose
whether to identify yourself but you should provide constructive feedback, balancing good points
and points where the student can improve. You should use the scenario and provide feedback to
the other student on their list of data objects, data attributes and summary document. You are free
to use whatever framework you like and the following should be minimum inclusions:

• Comment on the overall suitability of the data objects and attributes as an input for
database design and the summary document

• Provide constructive criticism on how the other student can improve their data objects and
attributes in future

• Provide some useful readings the other student may peruse that helps them develop their
understanding of data and data attributes

Submission Instructions:

Your spreadsheets and summary should be submitted by Thursday at midnight (Sydney time) of
week 4. Do not include any identifying information on your submission (i.e. not your student
number, name or anything else that might identify you). This is important because the peer review
is to be done anonymously. Non-submission or lateness will be treated in accordance with the late
assessment policy of the university.

Please note that late submissions mean that another student will effectively have less time to do
their peer assessment of your work.

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Learning Rubric: Assessment One

Assessment Criteria
Fail

(Unacceptable)
0-49%

Pass
(Functional)

50-64%

Credit
(Proficient)

65-74%

Distinction
(Advanced)

75 -84%

High Distinction
(Exceptional)

85-100%
Understanding of the
Data and Data
attributes

30%

Demonstrates limited
understanding of Data
and Data attributes.

Fair understanding of Data
and Data attributes
demonstrated. May
neglect to provide
resources or that these are
cursorily provided without
reference to specific areas
in the source.

Good understanding of
Data and Data attributes
demonstrated. May
provide a limited
number of sources the
peer can use to develop
their technique from.

Very good understanding of
Data and Data attributes
demonstrated. Makes
recommendations to other
external sources the peer can
access to develop their
understanding.

Outstanding understanding of
Data and Data attributes
demonstrated through
recommendation of other
sources with specific
references to components of
it that the peer will benefit
from.

Application and
Evaluation of the File
based database
management system

40%

Limited understanding of
the database
management system and
its applicability to
organization.

Understands the context
and impact the database
management system in an
organization and provides a
critique for the peer.

Understands the context
and impact the database
management system in
an organization.
Identifies logical flows
and questions the
viewpoints of the peer.

Evaluates the database
management system,
providing a critique of the
peer’s work, relevant to the
scenario. Identifies logical
flows and presents
suggestions the peer can use
to develop their technique.

Expertly evaluates the
database management
system presented by the peer.
Provides a thoughtful critique
in the context of the scenario
that the peer can use and
genuinely develop from.

Effective
communication

30%

Difficult to understand for
audience, no logical/clear
structure, poor flow of
ideas, argument lacks
supporting evidence.
Audience cannot follow
the line of reasoning.

Information, arguments and
evidence are presented in a
way that is not always clear
and logical. Line of
reasoning is often difficult
to follow.

Information, arguments
and evidence are well
presented, mostly clear
flow of ideas and
arguments. Line of
reasoning is easy to
follow.

Information, arguments and
evidence are very well
presented; the presentation is
logical, clear and well
supported by evidence.
Demonstrates cultural
sensitivity.

Expertly presented; the
presentation is logical,
persuasive, and well
supported by evidence,
demonstrating a clear flow of
ideas and arguments. Engages
and sustains audience’s
interest in the topic,
demonstrates high levels of
cultural sensitivity.

Assessment 1_602/ERD- ENTITY RELATIONSHIP DIASRAM (1)

Assessment 1_602/REPORT_ASSESSMENT_1 x
ASSESSMENT 1 MIS604

DATABASE MODELLING AND DATABASE DESIGNING

REPORT ON DATABASE OF THE TORRENS UNIVERSITY AUSTRALIA

Data is known as the facts or information that we are using every day for carrying our services. Whereas database is the collection of those facts or information and is found in an appropriate organized manner. Now when we are arranging our data or facts into a form of tables with rows and columns this process is known as the data modelling.
So, first of all, when I have started collecting the data about Torrens University, I have first draw ERD diagram, the major reason behind this was to get an idea about the relationship between the objects and their attributes. Thus, I have found that there are 4 main entities in this database, the University, Student, Course and Lecturer. Similarly, there are several attributes linked to these mentioned entities, such as, Student id, First name, Last name, Course Id, Course name, Lecturer name and so on. This is also known as a data modelling. Thus, drawing a diagram was an easy task, however, finding a relationship between them was a little tricky.
So, I have used crow’s notation to demonstrate their relationship and have used the bridge as well. Further up, now it is a time to put all the data into the table form into the excel spreadsheet. When I have started, I found it easy to distribute the data into rows and columns. I have used three different tables for each entity, student, course and lecturer.
The major reasoning using three different tables to avoid the mixing of data and further complexities. I have used, student Id, course id and lecturer Id as the primary keys to demonstrate the value of the all other related attributes. Also, there is a composite key that I have used to prevent data anomalies, which is a combination of Student ID and First Name. Moving further, in version one and two everything was going smoothly, I have deleted two rows easily followed by the addition of the 5 new rows, under those same attributes. So far, I did not face much issue.
However, the problem comes up when I moved to version 3, where I have to delete the two existing data rows and have to add two new attributes. An insertion and deletion anomalies occurred that leads to the data inconsistency. The reason is, student has got relationship with the course in which they have enrolled and with the lecturer who is teaching them. So, if we are deleting something in student table then it automatically got deleted from the course table and then from lecturer table as well. Likewise, while adding a new information into the student table, we have to update into another two tables as well.
Therefore, I preferred to apply the concept of normalization of the data to avoid any data inconsistency. This makes the database less complex and more informative.
Hence, the major part that I have done is I have further split the table using composite key, where I have easily added two new attributes without affecting data in the rows in the primary table. I have tried another way as well where I have just simply added two more columns with new attributes, but I have faced hurdle, as while I was deleting the existing rows, information in those table also got deleted and vice versa, creates a deletion anomaly. Therefore, to prevent this I have created two separate new tables with composite key, where I can easily add, update, insert and delete the data without affecting other tables.

Finally, reaching at fourth version, where, I have to delete the five existing attributes. I have deleted three attributes from student table, each one from the course and lecturer table respectively. Lastly, I have added five new rows with the data.
Overall, it was good experience, I got to know the concept of relationship within the entities and attributes. I have practically applied the normalization concept, found the anomalies within the database and taken the best possible step, by separating the table using composite key. I have also used color highlights to show the changes that I have made in the tables.

Assessment 1_602/TUA_DATABASE TABLE_ASSESSMENT 1.xlsx
Version 1

STUDENT STUDENT ID FNAME LNAME D.O.B COURSE COURSE ID COURSE NAME LOCATION LECTURER LECTURER ID FNAME LNAME

00229977T ALEX SMITH 12/1/95 MGT4068 PROJECT MANAGEMENT THE ROCKS TUA7711 JAMIE TIM

00229978T JOE BERNER 29/04/1989 MGT4069 BUSINESS COMMUNIACTION KENT STREET TUA7712 KEVIN CHIAN

00229979T JAMES ANDERSON 15/09/1991 MGT4070 BUSINESS ENVIRONMENT PYRMONT TUA7713 HEINZ HERMAN

00229980T RINA SHARMA 22/02/1986 MGT4071 SYSTEM ANALYSIS SYDNEY CBD TUA7714 JONNA BILLY

00229981T MOHAN KUMAR 13/05/1994 MGT4072 PROGRAMMING TOWN HALL TUA7715 RAKESH VERMA

00229982T MARIA BELLE 10/08/1889 MGT4073 STATISTICS AND MATHS PITT STREET TUA7716 ROWAN SYED

00229983T SUE XIANG 30/10/1990 MGT4074 STRATEGIC MANAGEMENT KENT STREET TUA7717 MO KADAR

00229984T XIO YANG 19/04/1985 MGT4075 DATA BASE MODELING THE ROCKS TUA7718 LEENA ROY

00229985T PETER ROBERT 20/01/1992 MGT4076 LANGUAGE AND LITERACY WYNARD TUA7719 MARINA JIN

00229986T MAX LEE 16/09/1987 MGT4077 COMPUTER SCIENCE CIRCULAR QUAY TUA7720 SHAH ROMIE

Version 1.2