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    What will this Programme do for you?

    Here are some specific challenges you can better address after earning your business and data analytics certificate:

    • 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

    Programme Modules

    • Identify strategic, managerial, and/or organisational problems related to analytics in your organisation or industry
    • Assess your organisation’s level of data analytical maturity
    • Articulate a plan for generating organisational value through improved analytical maturity
    • Identify high-value data analytics problems and use cases with your organization
    • Leverage existing and yet untapped data sources for your organisation
    • Evaluate your organisation’s data quality
    • Identify data summaries and visualizations relevant to your organizational needs and/or analytics goals
    • Identify factors that are important to consider in predicting a given business outcome
    • Identify the best analytical model to utilize for a given set of key outcomes and predictors
    • Evaluate most suitable accuracy metrics for your predictive analytics models
    • Specify ways to improve the accuracy of a model predicting a given business outcome
    • Evaluate organizational needs for data science personnel and data analytics infrastructure
    • Articulate differences between causal and predictive analytics
    • Identify causal analytics problems relevant to your organisation
    • Identify suitable cause and effect variables as well as confounding factors that could bias results
    • Learn about key models and methods to infer causal relationships among key business predictors and outcomes
    • Identify pertinent AI risks for your organisation and regulations in your industry sector relevant to these risks
    • Evaluate the current data protection infrastructure of your organisation
    • Identify factors that could compromise your organisation’s data integrity or model transparency


    Jussi Keppo
    Faculty at NUS Business School

    Associate Professor Keppo teaches risk management and analytics courses, and directs analytics executive education programmes at NUS Business School. He is also Research Director of the Institute of Operations Research and Analytics at NUS. Previously, he taught at the University of Michigan…

    Prasanta Bhattacharya
    Faculty at NUS Business School

    Prasanta is an Adjunct Assistant Professor with the Department of Analytics and Operations (NUS Business School). He holds a PhD in Information Systems from the Department of Information Systems and Analytics, National University of Singapore, where he studied computational social…

    Why Enrol for the Programme?

    Big data technologies continue to innovate how business is done. From booming tech start-ups like Grab and Ninja Van to top e-commerce players Lazada and Shopee, data analytics is being used across industries to supercharge efficiency, improve personalisation, and streamline operations.

    In this Business Analytics for Strategic Decisions programme delivered by NUS Business School, you can develop the tools you need to leverage your organisation’s most valuable data. Whether you’re a CEO, business manager or director, enhancing your analytics capabilities is essential to driving strategic decision-making and gaining a competitive edge.

    With modules focused on the predictive models used for business forecasting, the ins and outs of causal analytics, and the privacy and security of datasets, you will be exposed to big data applications, artificial intelligence (AI) technologies, and real-world case studies in this two-month business analytics programme.

    The NUS Business Analytics Playbook

    Participants will apply the learnings of the programme with the help of the Business Analytics Playbook. Here is an overview of what you can expect:

    • Each week, participants must complete the corresponding module’s application exercise in the Playbook
    • There will be optional polls, discussions, crowd-sourced activities, try-it exercises, and industry Q&As that participants are encouraged to engage with
    • Participants must complete 4 out of the 5 weeks of the Business Analytics Playbook in full, in order to receive their certificate

    The Playbook and application assignments are designed to seamlessly guide you through each module. Any questions you may have as you work through the Playbook can be addressed during the weekly Live Session’s assignment debrief.


    Upon successful completion of the program, participants will be awarded a verified digital diploma by Emeritus Institute of Management, in collaboration with MIT Sloan, Columbia Business School Executive Education & Tuck School of Business at Dartmouth.