2098 Big Data for Business Insight L5 Assignment 2025-26 | University College Birmingham

2098 Big Data for Business Insight L5 Assignment 

Assignment Task:

You are required to choose one public limited company in the retail industry and complete the tasks outlined below. 

• Demonstrate an understanding of Big Data within a retail context
• Evaluate relevant Big Data frameworks and tools
• Independently obtain and analyse a dataset containing at least two years of relevant data for the chosen retail company
• Identify key trends and generate meaningful insights from the data
• Critically examine ethical, privacy and security issues associated with the use of Big Data in retail
• Develop evidence-based strategic recommendations for the organisation

The dataset you download must be used for Section 4.
Your chosen retail company is used for all sections of this report

Background

Public limited companies in the retail industry increasingly depend on Big Data analytics to improve operations, enhance customer experience, optimise stock management, and strengthen decision-making. Understanding how Big Data is defined, stored, processed, analysed and governed is essential for supporting strategic growth in competitive retail markets.

Marking Criteria

Task Guidance

• Focus on attention to detail, quality of work and overall academic standards.
• Use Excel and Power BI as your data software.  
• For additional guidance on this assignment, please access the assignment vodcast available on Canvas.
• Support your findings with academic references
• Include tables, graphs, or visualisations
• Follow Harvard Referencing (Cite Them Right, 13th edition)

Structure of The Report

1. Introduction (approximately 200 words)

Introduce your chosen public limited retail company and outline the aims of the report. Explain the role of Big Data in modern retail operations, focusing on how analytics enhances decision-making, customer understanding, and strategic planning. Provide a brief overview of how the report will address Big Data concepts, frameworks, dataset analysis, ethical considerations and strategic recommendations

2. Big Data Definition, Warehousing and Storage (approximately 500 words)

Using your chosen retail company as the focus:

• Define Big Data in the context of your chosen retail company
• Explain Big Data characteristics
• Identify the types of data your company collects
• Explain data storage requirements
• Describe the role of data warehouses in supporting business insight

This section should demonstrate a clear conceptual understanding of Big Data within an applied retail scenario.

3. Big Data Frameworks and Tools (approximately 500 words)

You should compare at least two Big Data frameworks or tools- such as Hadoop, Spark, Business Intelligence platforms, cloud computing tools or data visualisation systems used by your chosen company. Your evaluation must be critical, not descriptive.

In your comparison, you should:

• Outline key features of each framework
• Explain their suitability for retail data
• Justify which one is most appropriate for your chosen company

4. Dataset Analysis (approximately 550 words)

You must obtain a minimum of two years of historical data relating to your chosen public limited retail company. The dataset must be publicly available and include measurable indicators relevant to retail operations, such as sales performance, product category data, customer purchasing behaviour, market demand, or digital engagement metrics.

Before conducting the analysis, you must provide a data dictionary that clearly defines the variables you have selected. The data dictionary should briefly explain:

• The name of each variable
• What the variable measures
• The unit of measurement, where applicable

Apply descriptive, diagnostic or predictive analytical techniques to your dataset. Present your results using clear visualisations and explain what the data reveals.

Examples of suitable analyses include:

• Annual or seasonal sales patterns
• Online versus in-store buying trends
• Product category performance
• Customer purchasing trends
• Geographic differences
• Relationships between price, volume and demand. 

This section should demonstrate your ability to work with real data and extract meaningful insights. This is the only section where the dataset is used.

5. Ethical, Privacy and Security Considerations (approximately 200 words)

Critically investigate the key ethical, privacy and security issues associated with Big Data in the context of your chosen retail company. Explain how ethical practice influences customer trust, fairness and business reputation.

6. Strategic Recommendation (approximately 250 words)

Using the insights from your dataset analysis (Section 4), propose a solution that creates value for your chosen retail business. This recommendation must connect directly to the findings in Section 4.

Learning Outcomes:

• Define Big Data and demonstrate an understanding of warehousing and storing of data.
• Compare and contrast the different frameworks that provide tools for performing Big Data tasks and be able to determine the best solution for a given business scenario.
• Investigate security and privacy issues and other ethical considerations with respect to Big Data.

General Assignment Guidance

UCB Standards for Presenting Your Written Work

• Main headings – Arial, size 14, bold, centred
• Sub-headings – Arial, size 12, bold, left-aligned
• Main text – Arial, size 12, left-aligned
• Margins – 2.5cm on all sides
• Spacing – 1.5 line spacing
• Between paragraphs – leave one line space between paragraphs
• Reference list – use single spacing. Leave one space between each reference
• Paper Size A4 (unless otherwise stated)
• Tables – label numerically in order of when they are presented in the assessment.
• Table 1, Table 2, etc.
• Charts/Graphs – label as Figure 1, Figure 2, etc
• Labels should be centred directly above Tables and directly below Figures in Arial, size 12

Teamwork and ITS Assessment

Should this assignment require you to work as part of a team, you will receive an individual grade based upon your performance as well as personalised feedback. The module leader will explain how your individual grade and feedback will be determined.

Importance of Word Count

Assignment word counts and presentation timings should always be observed. Ignoring a word count increases significantly the risk of your work losing marks because it lacks focus and clarity.  

Students will be required to state their word count on all submissions. A 10% leeway will be allowed – so the maximum a student should submit will be the word count + 10%.

The word count will exclude:

• The title page
• The contents page
• Models, graphs, data tables, and other exhibited figures or images 
• Lists of references

Appendices (these should be kept to a minimum)