| Category |
Coursework |
Subject |
Computer Science |
| University |
Ulster University |
Module Title |
COM745 Big Data & Infrastructure |
Coursework Assessment Overview
This module is assessed by two pieces of coursework.
Coursework 1 consists of a single in class examination which will have a time limit of 60 minutes. Coursework 1 contributes to 25% of the overall mark for this module.
Coursework 2 is a practical skills assessment wherein students need to develop a solution and create a related presentation plus a demonstrative video. Coursework 2 contributes to 75% of the overall mark for this module.
The university has several rules and regulations surrounding assessment, late submissions and illness. These are in the student guide [1] - ensure you read this and understand the impact of these rules and regulations.
These coursework assignments are detailed below.
Note: Students who submit coursework are declaring the following.
“I declare that this is all my own work. Any material I have referred to has been accurately referenced and any contribution of Artificial Intelligence technology has been fully acknowledged. I have read the University’s policy on academic misconduct and understand the different forms of academic misconduct. If it is shown that material has been falsified, plagiarised, or I have otherwise attempted to obtain an unfair advantage for myself or others, I understand that I may face sanctions in accordance with the policies and procedures of the University. A mark of zero may be awarded and the reason for that mark will be recorded on my file.”
Also note:
You will receive feedback as per University Guidance which is currently set at 20 working days after submission.
Coursework 1 – Practical Skills Assessment [25%]
Related learning outcomes:
- Demonstrate a comprehensive understanding of what is meant by big data and how a variety of database/data storage paradigms may be applied to address the challenges it presents.
During the delivery course of the module, students will be expected to complete a 60-minute, online test. This test will assess understanding of concepts that have been introduced and detailed until that point.
This exam will be set in the middle of the semester and will incorporate the following topics:
- General Database Concepts
- Relational Databases
- NoSQL Concepts
- Document Databases
- Time-series Databases
- Graph Databases
Coursework 1 will be delivered, submitted and assessed through the Blackboard online learning environment.
Coursework 2 – a set exercise [75%]
Related Learning Outcomes:
- Appraise the concepts behind a range of database/data storage paradigms and critically evaluate when to apply these paradigms to big data problems.
- Autonomously and independently investigate deficiencies when interacting with a range of technologies and leveraging knowledge of these deficiencies to improve future practice.
- Examine, select and autonomously apply skills to leverage data stored in a range of database/data storage paradigms.
The exercise will assess understanding of further concepts and demonstrate practical skills related to a data lake type environment, as taught within the module (such as Hadoop, Amazon EMR or Azure Data Lakes).
Students will be set an exercise where they will be expected to:
- Identify and evaluate several publicly available datasets related to educational attainment and nutritional quality. These may be from open sources such as kaggle.com, data.gov.in, data.gov, data.stats.gov.cn, or data.gov.uk
- Select appropriate datasets, as informed by their interests and the topic issued.
- Integrate and import these datasets into a suitable data lake system, as covered within the module, while providing a rationale for their choice.
- Perform meaningful analysis of the data to derive some simple useful information, as can be obtained by the dataset selected.
- Provide visualisation of the analysis through any data lake-associated technologies that the students deem suitable.
Once the solution is produced, students are required to produce a presentation that incorporates a 5-minute [indicative] video capture demonstrating the solution (NOTE: The video is to demonstrate the solution. It is not to be a recording of the slides being presented).
