Who should attend
Professionals, who are looking to improve functional performance through analytics or build business analytics capabilities to transform their organisation, will benefit most from this programme.
Understanding big data is an invaluable asset that can serve professionals in a variety of roles, including but not limited to:
- Director/Head of Operations
- Vice President
- Business, Data, or Financial Analyst
- Business, Project, or Strategy Manager
- Business, IT, Data, or Marketing Consultant
About the course
With big data technologies becoming more affordable and accessible, more and more companies are innovating how business is done. And as they innovate, more data piles up. Business analytics helps organisations to leverage their data to gain insights and make informed decisions. That’s why understanding these analytics is a vital first step for professionals who are looking to develop a strategic advantage and competitive edge in the market.
In order to build and implement the most effective business strategies, you must first identify the analytics-related barriers in your organisation and industry. For organisational goals to be met, analytical maturity must be improved through the continual assessment of data.
From predictive models used for business forecasting to the ins and outs of causal analytics to the privacy and security of datasets, participants will be exposed to big data applications, artificial intelligence (AI) technologies, real-world case studies, and insight into the analytics tools that can help bring agility to your organisation and enable data-driven decision-making.
WHAT WILL THIS PROGRAMME DO FOR YOU?
Here are some specific data analytics challenges you will better be able to address after taking the programme:
- Identifying analytics challenges and untapped data sources in your organisation or industry
- Articulating differences between causal and predictive analytics
- Evaluating and improving your organisation’s analytical maturity and quality
- Identifying suitable cause and effect variables and factors that could create biased results
- Assessing how measurements, people, and technology can be leveraged to meet organisational goals
- Pinpointing pertinent AI risks for your organisation and industry sector regulations relevant to these risks
- Identifying accuracy metrics and factors that are vital to predicting specific business outcomes
- Evaluating the current data protection infrastructure of your organisation
- Evaluating organisational needs for data science personnel and analytics technological infrastructure
- Recognising factors that could compromise your organisation’s data integrity or model transparency
- Module 1: Creating Organisational Value Through Data Analytics
- Module 2: Exploring Your Data
- Module 3: Predicting Business Outcomes
- Module 4: Inferring Causal Impact of Business Decisions
- Module 5: Privacy, Ethics, and Risk in the Data Economy
Professor Keppo teaches risk management and analytics courses, and directs analytics executive education programs at NUS Business School. He is also Co-Director of NUS Business Analytics Center. Previously, he taught at the University of Michigan. He has several publications in the top-tier jour...
Dr. Prasanta Bhattacharya is a Research Assistant with the Department of Information Systems & Analytics in the School of Computing at National University of Singapore (NUS). His research interests lie broadly in the area of computational social science, where he leverages statistical and com...
Videos and materials
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.