25-26 Group Work Assignment Remit
Programme Title：MSc Management
Module Title：Digital Business & Business Analytics
Module Code：37989
Assignment Title：Group Work Assignment
Level：PG - 20 credit module
Weighting：30%
Lecturers：Mohammad Delgosha
Hand Out Date：16/01/2026
Due Date & Time：19/03/2026 12pm
Feedback Post Date：20/04/2026
Assignment Format：Presentation
Assignment Length：8-10 minutes recorded video presentation
Team：Assignment Remit
You will be assigned to a small group to complete this assessment task. Group members will work together to source a dataset, preprocess, and utilise it to produce data visualisations and conduct descriptive analytics. The goal is to generate insights that would be valuable to a specific audience or for a defined purpose.
Requirement 1 –Tell a Data Story
You can scrape data from public websites where this is appropriate - but we are looking for rather large datasets (more than 500 observations/records with more than 8-9 variables/features) as a key element of your Data Story⎯not just a few numbers.2. Identify the Target Audience. Clearly define the target audience for your visualisations. Explain why this audience would be interested in the data and how they are expected to use it once provided.
3. Prepare the Dataset. The dataset you find may need restructuring, cleaning and editing to improve its quality and suitability for your purpose. You may use any tool to clean the data, including (but not necessarily limited to) Python, Excel or the data cleaning tools embedded in Tableau software.
4. Create Data Visualisations with Tableau. Use Tableau to create Data Dashboards that convey the key messages in the data to the target audience. Your presentation should explain these key messages. To undertake this part of the task you should use Tableau software and its features (dashboards, stories, etc) to design visual representations to effectively communicate the data's insights to the target audience. Use the interactive features of Tableau (filters or tooltips for example) where appropriate to make your data dashboard more insightful.
5. Supplement with Narrative. The Narrative in the Tableau file itself should supplement your visualisations and help convey key messages; it should not talk about the logistics of building your visualisation, your audience are not interested in that.
Requirement 2 –Your Presentation Structure:
2. Detail who the target audience is and the purpose for which they might use the data.
3. Explain the process you used to clean and edit the data. If you discarded any data say why this was done. If you merged datasets explain how and why you did this. Describe what problems you encountered and how you overcame them?
the needs of the audience?
5. Present key messages/insights conveyed by your data dashboard(s). Highlight key performance indicators that are critical or any patterns you found in the data that have managerial implications and can be used for data driven decision making.
Submission guidance:
1. Your Tableau data dashboard(s) should be submitted as a link at your presentation submission. This should link directly to the Tableau story that you have saved in the Tableau Public cloud gallery.
2. We also would like to see screengrabs of the Dashboard / story pages in your presentation file submission.
3. Provide links to the source dataset(s) you used - otherwise we cannot audit the validity of your data, and you will drop marks.
4. Your video-recorded presentation and presentation file should be submitted in the form of mp4 and ppt/pptx/pdf.
Module Learning Outcomes:
Grading Criteria:
|
Item No. |
Section |
|
Mark |
|
1 |
Dataset Selection |
- Have relevant dataset(s) been selected and are useful for the audience identified?
- Has this selection been justified?
- Is the dataset interesting and substantial (more than 500 observations/records with more than 8-9 variables/features)?
|
10 |
|
2 |
Target Audience and Purpose |
- Has the target audience been clearly identified?
- Is the purpose for which the audience might use the data explained?
- Is the dataset's relevance to the audience justified?
|
10 |
|
3 |
Data Cleaning and Editing Process |
- Has the data cleaning and editing process been thoroughly explained?
- Have appropriate techniques/tools been used to edit and clean the data? Is it clear why these techniques/tools were used?
- If any data was discarded or merged, has the reasoning been provided?
- Have challenges encountered and solutions implemented been described?
|
20 |
|
4 |
Visualization Design |
- Are the visualization designs appropriate for the data and audience?
- Have Tableau features (dashboards, stories, interactive elements) been effectively used?
- Are the visualizations clear and effective in conveying key messages?
|
20 |
|
5 |
Key Messages and Insights |
- Have key messages and insights been identified and presented?
- Are key performance indicators and patterns with managerial implications highlighted? - Are the insights useful for data-driven decision making? |
30 |
|
6 |
Submission Quality |
- Has a link to the Tableau data dashboard in the Tableau Public cloud gallery been included?
- Are screengrabs of the dashboard/story pages included in the presentation file?
- Have links to source dataset(s) been provided?
- Are the video-recorded presentation and presentation file good and in the correct format (mp4 and ppt/pptx/pdf)?
|
10 |
|
Total |
|
|
100 |
Ethical Use of Generative AI (GenAI):
• Researching and refining your ideas• Information retrieval or background research• Drafting an outline to organise or summarise your thoughts• Refining research questions• Checking spelling and grammar
Applying GenAI tools should be done with human oversight and control. You should carefully review and use the results carefully as AI can generate authoritative-sounding output that can be incorrect, incomplete, uncritical, or biased.
You may not submit any work generated by an AI tool as your own. Where you include any material generated by an AI tool, it should be properly declared just like any other reference material. Alongside your presentation file, you should also provide a commentary in the video-recorded presentation detailing how GenAI has been used to develop your final submission. If you have not used GenAI tools, you should clearly state so.
Plagiarism, including that which results from using GenAI, is a form of academic misconduct that will be dealt with under the University’s Code of Practice on Academic Integrity.
https://intranet.birmingham.ac.uk/as/libraryservices/asc/student-guidance-gai.aspx
Further Guidance:
Feedback to Students:
Both Summative and Formative feedback is given to encourage students to reflect on their learning that feed forward into following assessment tasks. The preparation for all assessment tasks will be supported by formative feedback within the tutorials/seminars.
Written feedback is provided as appropriate. Please be aware to use a web browser and not the Canvas App as you may not be able to view all comments.
Wellbeing, Extensions and Extenuating Circumstances:
The processes for extensions and extenuating circumstances (ECs) are to support students who have experienced unforeseen issues that have impacted their ability to engage with their studies and/or complete assessments. Students should notify Wellbeing of any extenuating circumstances as soon as possible via the online form, following the guidance provided. https://intranet.birmingham.ac.uk/social-sciences/college-services/wellbeing/index.aspx