Faculty: Prof. Ning Su

Associate Professor, General Management, Strategy & Information Systems, Ivey Business School

Learning outcomes:
This course is designed to offer an executive perspective on big data and related emerging technologies, and their impact on both private and public sectors. The course encompasses key concepts, analytical frameworks, real-life case studies, and future trends related to big data and digital technologies, with a focus on managerial decision-making in an increasingly digitized and globalized business environment. Specifically, we will examine the complexity of building technology platform for big data, analyze examples of leveraging big data in a competitive industry environment, discuss models and practices for acquiring big data capabilities, explore emerging markets and emerging technologies, and investigate the impact of big data on the future of global business, economy, and society.

Faculty: Prof. Xin (Shane) Wang

Assistant Professor, Marketing and Statistics, Ivey Business School

Learning Outcomes:

The first decade of the twenty-first century is the era of business analytics. The trends and innovations that have shaped the technology industry over the past several years. For example, Cloud computing has gone mainstream for many enterprises, and the Internet of Things (IoT) is changing how both industrial and consumer-oriented companies do business. The increasing popularity of social media has resulted in astounding growth in the amount of digital data available, Managers keep up to date on emerging digital information relevant to business. We are now determining how social media platforms can be leveraged to gain competitive strategy. This module will help you understand online behavior, firm advertising strategy, and market structure. The most important, the course identifies data sources that allow you to define and track performance indicators for your digital activities.  The goal is for students to learn frameworks and methods that will allow them to generate valuable and actionable business insights from common social media sources.

Faculty: Prof. Hailiang Chen

Associate Professor, Faculty of Business and Economics, HKU

Learning Outcomes:

Big data, artificial intelligence (AI), and blockchain are of strategic importance to companies and nations, as these key technologies have the potential to revolutionize many industries from financial services, healthcare, automobile to virtually every other industry. This module aims to give students a good understanding of these disruptive technologies and their real-world commercial applications, so that students may recognize the potential application of AI and Blockchain in their own businesses. Executives and managers wishing to learn more about or to monetize on AI and blockchain would find this module to be a valuable and insightful foundation on which they can pursue further inquiries.

Faculty: Prof. Haipeng Shen

Associate Dean (Executive Education), Patrick S C Poon Professor in Analytics and Innovation, Faculty of Business and Economics, HKU

Learning outcomes:
Firms are creating and consuming vast amounts of information, leaving behind a trail of digitized (big) data. To be successful, firms need to use the data to drive their decision-making, often under uncertainty due to incomplete information. However, much of the promise from the information-rich digital recording of firm activities has failed to materialize as managers often find it difficult to translate (big) data into actionable policies and generate business value. This module offers discussions at both strategical and operational levels. We start with the introduction of big data and artificial intelligence through examples. We then discuss the analytics triangle of Question – Data – Analytics, and the right balance among them needed for effective data-driven decision making. We demonstrate how to ask “crunchy” questions with cases and problem sharing from the participants, and then introduce analytics techniques using examples from operations analytics and healthcare analytics. We also hear from guest speakers/past programme participants and conclude with an outlook of the future modules.