Skills of Tomorrow for Data-Driven Operations and Logistics - BUSB7031

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2026 to 2027
Canterbury
Autumn Term 7 20 (10) Tuan Yu checkmark-circle
Canterbury
Autumn to Summer Terms 7 20 (10) Tuan Yu checkmark-circle
Canterbury
Spring to Summer Terms 7 20 (10) Tuan Yu checkmark-circle

Overview

Employers are in search for individuals who possess logical thinking, analytical capability, leadership, communication and the ability to work under pressure. Embark on a journey to explore contemporary and relevant issues that are changing the technological landscape of today. Develop your statistics and programming for business analysts skills and also soft skills such as communication, negotiation and writing skills to shape you into well-rounded business analytics professional.

Details

Contact hours

Lecture 16, Workshop 32, Independent Study 102, Assessment Preparation 50

Method of assessment

Python and statistics basics Assessment - (1500 words) worth 20%.
Apply SQL to a realistic business scenario, interpreting data to inform decision-making (1000 words) worth 40%. This Assessment is Pass Compulsory.
Build and interpret a Power BI report or dashboard (1000 words) worth 40%. This Assessment is Pass Compulsory.

Reassessment Method: Like for Like

Indicative reading

Learning outcomes

On successful completion of this module, students will be able to:

1. Critically evaluate the nature of data analysis and probability modelling, applying Python, Power BI, and SQL to conduct statistical analysis, data transformation, and visual exploration for informed decision-making.

2. Reflect on ethical considerations in business and management research, autonomously designing and implementing data analysis solutions using these tools that uphold integrity, transparency, and data governance standards.

3. Apply management and consultancy skills through critical thinking, problem analysis, and practical implementation, resolving real-world data challenges and delivering insights through integrated Python, Power BI, and SQL workflows.

4. Resolve challenges involved with working on real-world problems.

Notes

  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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