Master of Business Analytics

The Information Age we live in today has compelled all businesses to undertake global disruption and transformation, driven by data and analytics.

• A survey on the state of Data & AI from a list of 125 Fortune 1000 and Global Leadership Brands found that the percentage of organisations that had “created a data and AI-driven organisation” and “established a data and AI-driven organisational culture” both doubled (2X) in 2024.
• Worldwide AI spending is expected to total $644 billion in 2025, an increase of 76.4% from 2024, according to a forecast by Gartner, Inc.
• The global analytics market size was valued at USD 120.35 billion in 2024 and is projected to grow from USD 148.89 billion in 2025 to USD 600.46 billion by 2032.

The Master of Business Analytics curriculum is designed in collaboration with our industry partners to prepare students to develop sound knowledge and practical skills in data analytics for the challenges they will face as business leaders in the rapidly changing corporate environment. The program is taught as a combination of lectures and hands-on practical activities and case studies in our ‘Business Analytics Labs’ using state-of-the-art software used in large organisations. All ‘concepts’ will be delivered in the ‘context’ of business organisations across different industries namely retail, healthcare, banking, insurance, hospitality, travel and many others.

Theme 1 - Artificial Intelligence (AI): This includes techniques to simulate human decision-making through Machine Learning (ML) and Deep Learning (DL) algorithms. Students will learn to use ML and DL algorithms to solve various business problems such as pre-emptive prediction and prevention of fraud transactions in a bank, intelligent customer segmentation for marketing campaigns, and prevention of employee churn or burnout in organizations to name a few. Generative AI (GEN AI) and Large Language Models (LLMs) for business are also covered using Open AI’s GPT and Google Gemini models.

Learning Software used: SAS Viya, Python, R, Google Vertex AI and AI Studio

Theme 2 - Big Data: This includes the volumes of data lying around us including Structured Data, Semi Structured Data, Un-Structured Data. Students will learn to manage and use structured data from corporate database systems and spreadsheets, as well as with unstructured data from social media platforms, newspaper articles, corporate websites, images, and other forms of audio-visual data. Students will learn to build a data pipeline to ingest, store, clean, transform and process business data, whether in batch or real-time.

Learning Software used: Oracle Database for SQL, MongoDB for NOSQL, Google Cloud Storage and others

Theme 3 - Data Analysis and Visualization: This includes pre-processing, analyzing and visualizing data for gaining insights from complex information to make informed business decisions. Students will learn to build powerful data visualizations and interactive dashboards for communication with senior stakeholders and C-level suite of members and make recommendations about the direction of the business.

Learning Software used: Microsoft PowerBI, Microsoft Excel (Advanced), Google BigQuery

Theme 4 - Business Domain Knowledge: Students will gain knowledge of the business processes and functions such as Finance, Marketing, Operations etc. as well as macro factors such as Financial Markets, Consumer Markets and Policy Making, with a strong focus on sustainability and ethics.

Theme 5 - Industry-based practicum: This is an industry-based analytics project that is undertaken as the final component of the study program. Here, students will work on a real-life business case and develop an analytics solution in a live or a stimulated environment. Students will also gain access to the Google Cloud Platform (GCP) for Generative AI and Big Data Analytics solutions.

Students can choose to complete and achieve Professional Certificates from Google and/or Microsoft.