MIS602 Data Modelling & Database Design: Assessment Task

Tasks:

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. 

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.