Introductory description

In the new era of the "data economy", the value of high-quality, granular, and rich data assets is a critical success factor for transformative decision making in many industries and the leveraging of artificial intelligence (AI). This module aims to equip students with fundamental knowledge regarding the effective use of enterprise, web, and IoT data to meet the needs of modern organizations in the digital age and introduce technologies such as AI. The strategic value of data resources, as a means of enabling firms to achieve competitive advantage, is first considered, in order to understand the rationale behind the adoption of data management and business analytics practices. The challenges and opportunities of adopting various business analytics techniques, including using artificial intelligence for many analytical tasks, are investigated in order to obtain critical understanding of the building of organisational capability in these areas.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

• Strategic nature of data and relevant organizational practices and business models emerging from these.
• Management of data and relevant technologies (data warehousing, business intelligence practices, big data, IoT, etc.)
• Business Analytics techniques including visual analytics (use of software) and use in organisations for decision-making (business performance management, dashboards, etc.)
• Introduction of artificial intelligence, techniques, and applications (supervised/unsupervised learning, machine learning, clustering, etc.) Issues around the quality of data and bias, risks, ethical implications and business opportunities.

Learning outcomes

By the end of the module, students should be able to:

• Understand the strategic nature of enterprise, web and IoT data technologies and artificial intelligence
• Understand the managerial and organisational issues associated with the use of data and artificial intelligence practices
• Understand the software and methodology for developing data visualizations and the managerial issues associated with the selection and adoption of such data storage and manipulation technologies
• Be able to recommend management practices and measures to enable an organisation to exploit data assets and AI-related information technologies effectively

Indicative reading list

• Ohlhorst, Frank (2012). Big Data Analytics: Turning Big Data Into Big Money. Wiley and SAS Business Series.
• Marakas, G. (2003). Decision Support Systems in the 21st Century. (2nd ed.) Prentice Hall.
• Simon, Alan & Shaffer, Steven (2001). Data Warehousing and Business Intelligence for E-Commerce. Morgan Kaufmann Publishers.
• Marchand, D. and Davenport, T. (eds). (2000). Mastering Information Management. Prentice Hall.
• Skilton, M. and Hovsepian, Felix (2018) The 4th Industrial Revolution Responding to the Impact of Artificial Intelligence on Business, Palgrave Macmillan.

Subject specific skills

Be able to recommend management practices and measures to enable an organisation to exploit data assets and AI-related information technologies effectively.

Transferable skills

Written communication.
Oral communication.