Business Analytics

30 credits 

This module provides a comprehensive introduction to business analytics with a clear focus on developing data-driven decision-making skills through practical tools and applied statistical thinking. Structured around real-world business challenges, it equips you with the ability to extract insights, visualise patterns, and support strategic decisions using analytics.

The curriculum is designed to build sequentially across three pillars: data visualisation, statistical analysis, and forecasting. You will begin by exploring how business analytics addresses core problems in marketing, finance, and operations, before advancing into descriptive analytics, probability, regression modelling, and time series forecasting. Each topic is anchored in practical relevance, with examples from demand prediction, customer segmentation, sales optimisation, and campaign evaluation.

By the end of the module, you will be confident in applying key statistical methods, communicating insights through dashboards and reports, and designing models that inform performance and planning. The content is aligned with QAA benchmarks and BCS accreditation standards, supporting careers in business analytics, insight consultancy, and data-informed management roles.

Teaching and learning

This module adopts a blended, student-centred approach to support diverse learners and promote digital fluency, critical thinking, and professional competencies. Weekly delivery consists of one, one-hour lecture and a three-hour workshop each week.

Lectures focus on introducing core business analytics concepts, statistical methods, and data interpretation frameworks. Pre-recorded video tutorials and digital resources are made available prior to each session to support flipped learning, enabling you to engage confidently with upcoming topics. In-class time is dedicated to discussion, real-world case analysis, and reflective dialogue to encourage critical thinking and collaborative learning.

Workshops offer hands-on practice with tools in Excel. You will solve realistic, sector-relevant problems (e.g. retail, healthcare, public services), developing your technical skills while enhancing business understanding. Tasks are scaffolded starting with guided exercises and progressing to open-ended challenges to support the transition to postgraduate-level learning.

You will also have an additional 30 minutes of online support each week to enhance your understanding and learning.

Assessment

This module will be assessed by a multiple-choice test (30%) and a business analytics report (70%).

30 credits 

This module provides you with a strategic and conceptual foundation in business intelligence (BI), focusing on how organisations leverage data and AI to enhance decision-making, performance, and innovation. 

You will explore the full BI value chain from data acquisition and governance to insight generation and executive reporting - through the lens of emerging AI capabilities. The curriculum is structured around real-world business applications, allowing you to critically evaluate how BI systems and AI technologies are reshaping operational and strategic practices across industries.

Rather than focusing on technical tool training, the module emphasises high-level understanding of BI systems, data storytelling, and the organisational conditions necessary for successful BI adoption. Through business case studies and simulated scenarios, you will examine key topics including data governance, leadership in analytics transformation, AI-augmented decision-making, and ethical use of data and algorithms.

You will also explore how AI applications such as predictive modelling, natural language processing, and generative AI are integrated into modern BI strategies. A capstone group project will challenge you to design a BI roadmap for a simulated organisation, demonstrating your ability to link data strategy with business value creation.

By the end of the module, you will have developed the skills to evaluate BI and AI initiatives from a managerial perspective, communicate data-driven insights to non-technical stakeholders, and lead BI adoption within a business setting.

The module prepares you for strategic roles such as BI Consultant, Insight Manager, or Analytics Translator roles that require not only data fluency but also leadership and communication skills essential for business transformation in the AI era.

Teaching and learning

This module adopts a practice-based, exploratory learning approach that empowers you to transform raw data into meaningful, visual, and actionable business insights. The teaching structure blends theory, software application, and real-world business cases to develop your technical and storytelling capabilities using industry-standard BI platforms like Tableau and Power BI.

Weekly teaching will typically involve one, one-hour lecture and a three-hour workshop (which includes tutorial and lab sessions).

Lectures introduce the foundations of data visualisation theory, dashboard design, and the principles of effective business intelligence (BI). You will explore best practices in visual encoding, data ethics, visual literacy, and the strategic use of dashboards for business performance monitoring, reporting, and decision-making. Theoretical content is always contextualised using real organisational examples (e.g. KPIs, sales performance, operational dashboards).

Hands-on workshops form the core of the module delivery, providing structured and guided experience using Tableau and Power BI. You will develop dashboards with slicers, drilldowns, filters, and calculated fields, applying them to various business domains (marketing, finance, operations, HR). As the course progresses, you will move from structured tasks to open-ended scenarios, allowing you to design bespoke dashboards that meet real business needs.

Tutorials offer additional support for skill development and assessment preparation, focusing on data preparation, interface design, user experience, and translating complex datasets into clear, decision-ready visualisations. Tutorials also provide feedback and coaching tailored to individual progress and group project work.

The module is structured progressively, beginning with visualisation principles and basic dashboard construction, and advancing toward multi-source integration, interactivity, and storytelling for senior business audiences. The learning environment encourages peer collaboration, creativity, and critical thinking around how visual analytics can influence strategic outcomes.

Assessment

This module will be assessed by group coursework (30%) and case studies (70%).

30 credits 

This module centres on the executive-level application of analytics and data-driven thinking in business decision-making. It prepares you to bridge the gap between complex data analyses and strategic business decisions.

You will examine how organisations can formulate and support strategy using data, exploring frameworks of decision science and evidence-based management.

Key themes include aligning data analytics initiatives with business objectives, evaluating strategic opportunities and risks through data, and developing policies for data governance at the leadership level.

Rather than focusing on technical coding, the emphasis is on interpreting analytical outputs (such as trends, forecasts, and models) and integrating those insights into high-level decision processes. Through case studies of companies using analytics for competitive advantage, you will learn to identify where data can add value in strategic planning and how to communicate recommendations to C-suite stakeholders in clear, persuasive ways.

The module covers methodologies such as decision frameworks, scenario planning, and prescriptive analytics (optimisation and simulation) from a management perspective. Attention is also given to the ethical and organisational challenges of data-driven strategy – including data privacy, bias in algorithmic decisions, and building a data-informed culture.

By the end of the module, you will be equipped with the knowledge to formulate data-driven strategies, make informed executive decisions based on data insights, and lead initiatives that embed analytics into an organisation’s strategic outlook.

By the end of the module, you will be prepared to:

• Examine data-driven decision-making in formulating business strategy and policy
• Aligning data strategy with organisational strategy – developing data strategies that support business goals and competitive advantage
• Building a data-driven culture – the leadership role in fostering an organisational culture that values analytics, addresses resistance to data-driven practices, and invests in analytical capabilities.

Teaching and learning

This module adopts a blended and applied learning approach designed to build strategic thinking, data literacy, and executive communication skills. The structure emphasises critical evaluation, real-world business application, and interdisciplinary learning.  

Weekly teaching will typically involve one, one-hour lecture and a three-hour workshop (which includes tutorial and lab sessions).

Lectures introduce key frameworks and concepts in strategic decision-making, such as evidence-based management, decision science, scenario planning, and prescriptive analytics. Sessions focus on interpreting data insights to support high-level business decisions and strategy formulation. Contemporary case studies and business simulations are used to contextualise abstract concepts, encouraging critical reflection on real-world data-driven strategy and the role of leadership in analytics adoption.

Workshops and interactive sessions guide you through practical exercises in strategic planning using analytics outputs. These include exercises in interpreting dashboard outputs, evaluating forecasting results, and simulating business scenarios using decision frameworks. Group activities foster collaborative analysis and peer discussion around ethical dilemmas, governance decisions, and risk-based strategic choices.

Tutorials offer small-group and one-to-one support to help you refine your strategic thinking, aligning your coursework with real-world expectations, and receive formative feedback on developing ideas. Tutorials also focus on preparing you to communicate complex data-driven insights to executive-level stakeholders in accessible and persuasive formats.

The module is structured progressively, beginning with visualisation principles and basic dashboard construction, and advancing toward multi-source integration, interactivity, and storytelling for senior business audiences. The learning environment encourages peer collaboration, creativity, and critical thinking around how visual analytics can influence strategic outcomes.

You will also have an additional 30 minutes of online support each week to enhance your understanding and learning.

Assessment

This module will be assessed by a group AI business project and presentation (30%) and an individual AI case study and code submission (70%).

30 credits

This module equips you with the skills and knowledge to harness data for informed marketing decision-making.

You will explore key analytical tools and techniques, including Microsoft Excel and Google Analytics 4 (GA4), to identify patterns, trends, and seasonality in marketing data. You will explore essential consumer metrics such as Customer Lifetime Value (CLV) and Net Promoter Score (NPS), analyse campaign performance using advanced Excel functions, and develop predictive models through linear regression.

You will be introdcued to web analytics, social listening, sentiment analysis, and big data concepts, enabling you to evaluate consumer behaviour and design data-driven marketing strategies.

Along with gaining analytical expertise, you will also engage in case study analysis, group discussions and PowerPoint presentations to gain comprehensive problem-solving skills, teamwork experience, and the ability to effectively communicate insights to diverse audiences.

Teaching and learning

The teaching delivery on this module consists of one hourly and one three hour workshop per week.

Lectures will cover all the key concepts and theories around data-driven marketing strategies, marketing analytics tools, big data, actionable insights advanced Microsoft Excel and GA4. 

Seminars will be computer lab-based, providing you with hands-on experience in using analytical tools and applying your learning to real-world datasets The module focuses on generating actionable insights by translating complex consumer data into effective marketing strategies and campaigns.

Assessment

This module will be assessed by an individual report (70%) and a group presentation (30%).

60 credits

You will apply your knowledge to a real-world business setting.

You will choose from three career pathways:

1. Consultancy challenge – collaborating with international businesses, NGOs, and community organisations, through a structured consultancy challenge, you will work in teams to tackle real-world business problems. This hands-on experience not only strengthens your professional skill set but also enhances your professional and social capital and competitiveness in the global marketplace.
   
   
2. Research internship - as a research intern, you will undertake a small research project under the supervision of experienced researchers from our Centre for Sustainability and Responsible Management. You will experience projects that are beneficial for a wide range of stakeholders, including local and central governments, businesses and charitable organisations.
   
   
3. Start-up pathway - if you're interested in becoming a entrepreneur, this pathway is specifically designed to support you with developing of a new venture idea.