BS510 L7 Data Design Management : DDM Jan26 Assessment Brief  | University of Law

ASSESSMENT BRIEF

L7 Data Design Management 

Key Details and Requirements 

Learning outcomes:

1. Understand the role, impact, collection and usage of data and how it shapes company strategies.
2. Understand and critically evaluate how progress in data storage technologies based on relational database management systems can shape and change business models in the corporate world and society in general.
3. Understand and apply appropriate theoretical concepts, tools and techniques to design appropriate data management processes and data models to apply them in business contexts using SQL.
4. Critically evaluate different technologies widely used in the market to process data and transform it into knowledge.
5. Apply the acquired technical skills to create powerful reports based in the objective analysis of the data sources, combining analytics and visual presentations.

Declaration:

By sitting this assessment, I am confirming:

• That I have worked independently on this assessment submission, and I have not worked together with any current or previous student at the University to produce my submission, other than when officially permitted to do so.
• I also confirm the contents of my submission have not been generated by a third party.
• I have fully referenced and correctly cited the work of others, where required.
• I have not used any generative AI tools to generate, rephrase or otherwise produce content for this submission, except where their use was explicitly permitted, and I have read and understood the University's AI in Higher Education Policy and Protocols.
• I have read the Student Discipline Regulations and understand that any academic misconduct can lead to disciplinary consequences and undermine academic integrity.
• I understand that where applicable, I am expected to engage with my academic work in a manner that meets the professional standards and requirements set by the relevant Professional, Statutory and Regulatory Body (PSRB) or accrediting body for my course.

By submitting this assessment, I am confirming that I am fit to sit according to the Assessment Regulations.

Assessment details: Individual presentation with explanatory notes, 100% (equivalent to 2,500 words) required to be submitted as pdf document (slides + explanatory notes) through Turnitin.

Referencing: Students are expected to use Harvard Referencing throughout their assignments where required. Please follow the Harvard Referencing Handbook for all your assignments at the ULBS.

Submission Method: Turnitin - Your work will be put through Turnitin. All submissions will be electronically checked for plagiarism.
You have the option to upload your work ahead of the deadline, more than once. ULBS will be reviewing your last submission only. You can only upload one file. For example, if your work contains a word document and power point slides/Excel spreadsheet you will need to copy your slides/spreadsheet into the word document.

ULBS Assessment Office Contact Details

The ULBS Assessment Office are here to help should you have any non-academic questions related to your assessments. You can contact them at AssessmentOffice@law.ac.uk

Note: Keep in mind that self-plagiarism (when you reuse your own specific wording and ideas from work that you have previously submitted without referencing yourself) is also a form of plagiarism and is not allowed.

ASSIGNMENT DETAILS

You have been appointed as a Data Strategy & Analytics Consultant for SwiftWheel Mobility Solutions, a fictitious electric scooter-sharing service operating in UK. The company operates in a growing network of cities, including London, Leeds, Cardiff, and Edinburgh. SwiftWheel’s mission is to provide fast, eco-friendly, and affordable micro-mobility options for short urban commutes, helping reduce traffic congestion and carbon emissions. 

SwifttWheel collects large volumes of data daily from sources:

• Mobile app registrations
• Scooter rentals & returns
• Maintenance logs
• Customer feedback forms
• Payment transactions
  The management team wants to use ‘data as a strategic asset’ for the following assumptions: to improving fleet management, optimise operations, and increase customer retention. As this is a simulated scenario, you will work with:
• Hypothetical operational processes and data structures based on above mentioned assumptions.
• Publicly available market information to support your industry comparisons.
• Synthetic datasets that you create yourself for database population and pipeline integration.

You have been tasked to:

• Evaluate SwifttWeel's current data practices (based on a reasonable and fictionalised description)
• Design and implement a robust relational database for improved operations
• Develop a small-scale data pipeline to integrate, clean, and transform multiple data
  sources for decision-making

You are expected to complete the following tasks:

Task 1 (LO1, LO2): Current state and Industry Context

• Describe SwiftWheel’s current state: how likely data is collected, stored, and used (based on sources and assumptions).
• Conduct SWOT analysis, comparing SwiftWheel with one real-world mobility company (e.g., Lime, Tier, Bird, Bolt) using public information.
• Critically evaluate modern RDBMS advancements available in the industry (e.g., cloud SQL, distributed systems) and explain their potential impact on SwiftWheel’s business model.

Task 2 (LO3): Database Design & SQL Implementation

Using relational modelling principles:

• Identify key business entities: customers, scooters, trips, maintenance, payments, staff etc.
• Draw a prospective current-state data flow diagram showing how data moves from collection points to storage and reporting (e.g. customers, trips, maintenance, payments) clearly demonstrating any ETL approach.
• Create a future-state ER diagram with entities, attributes, keys, relationships, and cardinality.
• Apply normalisation possibly up to 3NF.
• Implement the database in SQL:
  oCreate tables with appropriate constraints and outputs (include the table
  outputs)
  oInsert at least 10 sample records per table (synthetic but realistic data; vary by city, membership type, product category) (include the outputs)
  oWrite SQL queries to answer at least five business questions with outputs, such as:
• Which city has the highest trip volume this month?
• Average trip duration by membership type
• Number of maintenance requests completed per technician
• Customers with overdue payments
• Most frequently used scooter models
  o Implement at least one transformation approach using query optimisation
  (e.g., merging tables, cleaning maintenance data, or creating monthly revenue summaries etc.) on database and provide before-and-after samples.

Task 3 (LO4, LO5): Technology Transformation and Analytics

• Select two technologies widely used for data processing and transformation (e.g., Apache NiFi, Talend, Python Pandas, Power Query, AWS Glue).
• Critically evaluate their capabilities (in tabular form) for data integration, cleaning, transformation, and automation, considering SwiftWheels' needs. Justify your final choice (from one of the selected technologies) for implementation.
• Use the transformed dataset (in Task 2) to answer any two management questions (e.g., improve fleet management, optimise operations, increase customer retention, city expansion priorities, customer retention risks etc.), presenting outputs with short interpretations.

Important:

Proposed slides

Below mentioned is the proposed structure with number of slides which can be adjusted according to the development of work.

• Slide 1 (Cover page)
• Slide 2 (Table of contents)
• Slide 3 (Introduction)
• Slide 4 – 6 (Task 1)
• Slide 7 – 18 (Task 2)
• Slide 19 – 21 (Task 3)
• Slide 22 (References)
• Slide 23 (Appendix)

Format & structure

• Organise all tasks into a PowerPoint presentation.
• Provide detailed explanatory notes for each slide (use the Notes section in PowerPoint).
• Save and submit the final version as a single PDF document (slides + explanatory notes).

Database & SQL (Specifically for Task 2)

• Show SQL query outputs on the relevant slides.
• Place the SQL scripts in the explanatory notes section for clarity.

Appendix slide

• Include appendix slide containing the complete SQL script file (drag & drop).

Submission

• Submit the final PDF document through Turnitin.

Please refer to the marking criteria (below) for a breakdown of how the tasks will be marked.

BS510 DDM Assessment Criteria