What are the recent advancements and applications of BIG DATA in the industry of your choice? What are the limitations? Conduct in depth literature review.

Student Assignment Brief

This document is intended for Coventry University Group students for their own use in completing their assessed work for this module. It must not be passed to third parties or posted on any website. If you require this document in an alternative format, please contact your Module Leader.

Contents:

• Assignment Information
• Assignment Task
• Marking and Feedback
• Assessed Module Learning Outcomes
• Assignment Support and Academic Integrity
• Assessment Marking Criteria

The work you submit for this assignment must be your own independent work, or in the case of a group assignment your own groups’ work. More information is available in the ‘Assignment Task’ section of this assignment brief. 

Assignment Information

Module Name: Contemporary Issues in Big Data

Module Code: 7032SSL

Assignment Title: Enhancements and limitations associated with BIG DATA Assignment Due: 07/04/25 at 18:00 UK time

Assignment Credit: 10 credits

Word Count (or equivalent): 2000 words +/- 10%

Assignment Type: Percentage Grade (Applied Core Assessment). You will be provided with an overall grade between 0% and 100%. You have one opportunity to pass the assignment at or above 40%.

This document is intended for Coventry University Group students for their own use in completing their assessed work for this module. It must not be passed to third parties or posted on any website.

Assignment Task

This assignment is an individual assignment which requires you to write a 2000-word original report. Work on the same industry as you worked on in CW1, choose one company then address the following questions:

1. What are the recent advancements and applications of BIG DATA in the industry of your choice? What are the limitations? Conduct in depth literature review.
2. Analyse the tools and techniques that company of your choice is utilising to manage their BIG DATA collection, preparation and processing. Examine how these tools and techniques give the company competitive advantages? How they impose limitation.
3. Critically evaluate the social, legal and ethical dilemmas associated with big data in the company. Evaluate their practices and make evidence-based, research-based recommendations to improve them.

Your report should be based on academic research and industry case illustrations

This assessment is categorised as AMBER for the use of AI.

You may use AI for the following

• Inspiration: using AI tools to generate research questions or topic.
• Planning and management: using AI tools to suggest a title, structure, subheadings, or themes, to generate templates, to suggest processes for task management, or to generate prompts to assist thinking through assessment structure or task management.
• Sources and data collection: using AI tools to suggest sources.
• Summarising and consolidating notes: using AI tools to summarise notes or to consolidate notes.
• Translation: using AI tools to translate small sections of your written or recorded work into the language(s) used in an assignment
• Presentation: using AI tools to present data in an accessible format such as by generating, graphs, charts, tables, slides, images, word-clouds, animations, or captions.
• Checking: using AI tools to proofread or check work. 

Submission Instructions:

• Individual submissions
• The word count is 2000 words. There will be a penalty of a deduction of 10% of the mark (after internal moderation) for work exceeding the word limit by 10% or more. The word limit includes quotations and citations, but excludes the references list.
• Permitted submission formats is Microsoft Word) PDF is not acceptable. Please ensure that you have submitted your work using the correct file format, unreadable files will receive a mark of zero.

The assessment must be submitted by 07/04/25 at 18:00 UK time. No paper copies are required. You can access the submission link through the module web.

• Your coursework will be given a zero mark if you do not submit a copy through Turnitin. Please take care to ensure that you have fully submitted your work.
• All work submitted after the submission deadline without a valid and approved reason (see below) will be given a mark of zero.

This document is intended for Coventry University Group students for their own use in completing

• The University wants you to do your best. However, we know that sometimes events happen which mean that you can’t submit your coursework by the deadline – these events should be beyond your control and not easy to predict. If this happens, you can apply for an extension to your deadline for up to Five Working Days, or if you need longer, you can apply for a deferral, which takes you to the next assessment period (for example, to the resit period following the main Assessment Boards). You must apply before the deadline.

You will find information about the process and what is or is not considered to be an event beyond your control at https://share.coventry.ac.uk/students/Registry/Pages/Deferrals-and- Extension.aspx

• Students MUST keep a copy and/or an electronic file of their assignment.
• Checks will be made on your work using anti-plagiarism software and approved plagiarism checking websites.
• You need to acknowledge how you have used any AI tool by inserting a table as per the example below before your list of references:

Marking and Feedback

Your assignment will be marked by the module team. Provisional grades will be released once internally moderated. Feedback will be provided by the module team alongside grades release. Feedback will be accessible through Turnitin via Aula. Details of the marking criteria for this task can be found at the bottom of this assignment brief. 

Assessed Module Learning Outcomes

The Learning Outcomes for this module align to the marking criteria which can be found at the end of this brief. Ensure you understand the marking criteria to ensure successful achievement of the assessment task. The following module learning outcomes are assessed in this task:

LO2-Critically identify and evaluate the social, legal and ethical dilemmas associated with big data.

LO3-Evaluate how big data analysis is applied within a business context in support of business problems. 

Assignment Support and Academic Integrity

If you have any questions about this assignment please see the Student Guidance on Coursework for more information.

Spelling, Punctuation, and Grammar:

You are expected to use effective, accurate, and appropriate language within this assessment task.

Academic Integrity:

The work you submit must be your own, or in the case of groupwork, that of your group. All sources of information need to be acknowledged and attributed; therefore, you must provide references for all sources of information and acknowledge any tools used in the production of your work. We use detection software and make routine checks for evidence of academic misconduct.

It is your responsibility to keep a record of how your thinking has developed as you progress through to submission. Appropriate evidence could include: version controlled documents, developmental sketchbooks, or journals. You should regularly save your work to your university OneDrive account. This evidence can be called upon if we suspect academic misconduct.

If using Artificial Intelligence (AI) tools in the development of your assignment, you must reference which tools you have used and for what purposes you have used them. This information must be acknowledged in your final submission.

Definitions of academic misconduct, including plagiarism, self-plagiarism, and collusion can be found on the Student Portal. All cases of suspected academic misconduct are referred for investigation, the outcomes of which can have profound consequences to your studies. For more information on academic integrity please visit the Academic and Research Integrity section of the Student Portal.

Support for Students with Disabilities or Additional Needs:

If you have a disability, long-term health condition, specific learning difference, mental health diagnosis or symptoms and have discussed your support needs with health and wellbeing you may be able to access support that will help with your studies.

If you feel you may benefit from additional support, but have not disclosed a disability to the University, or have disclosed but are yet to discuss your support needs it is important to let us know so we can provide the right support for your circumstances. Visit the Student Portal to find out more.