BUS7063 - Data-Driven Decision-Making in Business

Objectives:

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

1 - Examine and implement advanced data integration, analysis and visualisation techniques to address complex business problems and support informed decision-making
2 - Apply and adapt various digital tools to generate actionable insights and effectively communicate these through interactive reports and dashboards
3 - Assess and interpret the strategic implications of analytical findings, critically evaluating their ethical, organisational and societal impacts
4 - Plan and deliver a data-driven project, demonstrating the ability to integrate diverse data sources, conduct in-depth analysis and propose business strategies, with a critical evaluation of outcomes.

Content:

The Data-Driven Business Analytics module builds on strategic analytics skills, focusing on the application of digital tools to address real-world business challenges. Students learn to integrate, analyse and visualise data to support strategic decision-making. The module introduces key concepts in advanced analysis, enabling students to forecast trends and optimise resources. A high-level introduction to machine learning highlights its relevance in driving business innovation. Through case studies and practical exercises, you develop skills in data-driven decision-making, ethical analytics and presenting actionable insights to stakeholders, ensuring they are prepared for analytics-driven roles in modern organisations. This module is designed to incorporate interdisciplinary approaches, combining principles from business and computer science to tackle complex challenges in modern organisations. By bridging these disciplines, you gain a comprehensive understanding of how data-driven strategies can inform business decision-making while utilising technological advancements.

Learning and Teaching Information:

The learning and teaching methods include lectures, which provide strategic concepts such as business intelligence and predictive analytics. Workshops with a seminar element offer hands-on experience with real datasets using industry tools, alongside interactive activities such as case studies, role-play exercises and group discussions. Independent learning enables you to deepen your understanding through guided reading, research and project work. Additionally, you will benefit from guest lectures, ensuring real-world relevance and alignment with current business practices. This balanced approach integrates theoretical, practical and independent learning, providing a comprehensive educational experience that prepares you for data-driven decision-making in professional environments.

Lectures
Hours: 20
Intended Group Size: Cohort

Workshops
Hours: 20
Intended Group Size: 5-10

Guided independent study
Hours: 260

Further Details Relating to Assessment

In this individual assignment, you will produce an Applied Data Visualisation and Strategy Report that demonstrates your ability to apply data-driven decision-making in a real-world business context. You will select a publicly traded company or a large private organisation and independently analyse publicly available data (such as financial statements, industry reports and market trends) to uncover insights relevant to strategic decision-making.

The emphasis is not only on your ability to analyse and interpret data but also on how effectively you design visualisations, communicate insights and translate your findings into actionable business strategies. This assessment builds upon the analytical foundation developed in the Strategic Business Analytics module, encouraging you to advance your skills in data storytelling and strategic thinking, with a strong focus on applying insights to support real business decisions.

Formative assessment and feed-forward methods will be employed throughout this module at various points in the term. Formative forms of assessment will include (but not exclusively): class-based activities, opportunities for draft pieces of work to be submitted for comments and feedback, drop-in sessions with the module tutor and peer-assessed (non-credit bearing) group activities.

Comprehensive assessment guidelines, including submission deadlines and grading rubrics, are available within the Module Handbook.

Assessment:

001 Applied Data Visualisation and Strategy Report; 5000 words or equiv; End of term 1 100%

Fact File

Module Coordinator - Ali Hayder
Level - 7
Credit Value - 30
Pre-Requisites - N/A
Semester(s) Offered - 7PGS1

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