This module introduces the fundamentals of business analytics and their role in supporting organisational decision-making. Learners will explore the interplay between data analysis and human judgment, and understand the importance of distinguishing between populations and samples when interpreting data. Practical considerations for planning analytics projects within organisational constraints are also discussed.

This module explores how organisational structures, legal frameworks, cultural norms, and ethical principles shape data practices and decision-making. Learners will gain insight into key regulations like GDPR, the importance of cultural awareness, and frameworks for ethical data use. Practical examples and guidelines help clarify what is permissible and responsible when working with data.

This module introduces the foundational steps for working with organizational data, including identifying data sources, understanding data structures, and applying essential cleaning techniques. Learners will explore how to classify variables, handle missing or problematic data, and prepare datasets for effective analysis and visualization.

This module introduces key analytical techniques for quantifying qualitative data, performing statistical tests, and making data-driven decisions using Excel. Learners will explore how to answer different types of business questions, interpret statistical significance, and apply regression analysis for prediction. Practical Excel skills are emphasized throughout to ensure hands-on experience with real-world data analysis.

This module guides learners in effectively communicating analytical results by considering audience knowledge, project objectives, and data visualization best practices. You will explore how to select and design impactful visualizations, craft clear narratives, and evaluate the effectiveness of your data-driven communications.

This module introduces the use of analytics in marketing, focusing on how data-driven insights inform decisions about market opportunities, customer segmentation, pricing, distribution, and communication strategies. Learners will explore practical applications of analytics to optimize marketing effectiveness and address common challenges in data collection and interpretation.

This module introduces the use of data analytics in human resources to measure employee performance, monitor diversity and inclusion, assess training effectiveness, and support talent acquisition. Learners will discover how data-driven insights can inform equitable and effective HR practices. Practical examples and common data sources are explored to help you understand real-world applications.

This module explores how organizations leverage analytics to optimize supply chain management, enhance sustainability, implement predictive maintenance, and detect fraud. Learners will gain insights into key data sources, analysis techniques, and ethical considerations relevant to operational analytics. Practical examples illustrate how analytics can be tailored to diverse organizational needs.

This module explores how data analytics can inform financial decision-making across marketing, HR, and operations. Learners will discover how to assess the financial impact of organizational activities, evaluate overall financial health, and apply analytical techniques to real-world business scenarios. Practical examples and case studies illustrate how analytics can drive more informed, data-driven financial strategies.

Explore how emerging technologies like IoT, AR, VR, AI, and edge computing are transforming the landscape of data analytics. Learn about the implications for privacy, data processing, and new career opportunities in this evolving field.