This module provides students with a comprehensive understanding of big data analytics in business decision-making. It introduces the drivers of data-driven transformation and business intelligence, while equipping students with applied knowledge of key analytical approaches and machine learning methods. Through case studies in finance, marketing, and operations, students learn to translate data into actionable strategies and critically evaluate ethical, privacy, and governance issues associated with big data.
A. Understand the concepts, motivations, and challenges of big data adoption in business. B. Identify, compare, and apply data analysis techniques to solve domain-specific business problems. C. Evaluate big data analytical models and translate them into clear managerial insights and recommendations. D. Reflect on ethical, privacy, and governance issues related to big data adoption, and assess responsible practices in data-driven decision-making.
The module is delivered primarily through instructor-led lectures, including practice-based sessions, supported by tutorials to reinforce fundamental concepts in big data analytics. Case studies are used to illustrate the application of these techniques to real-world business problems. Students are expected to attend two hours of formal lectures and one hour of tutorial sessions in a typical week. In addition, they should devote sufficient time to self-directed study, reflecting on lecture materials and completing background reading.