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    Business Analytics: Decision Making through Excel
    National University of Singapore Business School

    Business Analytics: Decision Making through Excel

    National University of Singapore Business School, Singapore
    HomeData & AINational University of Singapore Business SchoolBusiness Analytics: Decision Making through Excel
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    online · Instructor-Led
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    $3,107

    All-inclusive program fee

    About This Program

    We are now in the era of big data. Companies are able to collect a tremendous amount of data, very often more than necessary, with ease at an inexpensive cost. "Information is Power" is no longer valid if companies are not able to make correct decisions timely on the basis of the data on hand. The use of business analytics for modelling and decision making represents the future of best practices for tomorrow's companies. This course prepares participants with fundamental theory and skills to capture business insights from data for decision making using Excel Spreadsheets. Practical examples and cases with data are used to stimulate participants' interest and foster their understanding of the use of Business Analytics in management and business. Quantitative models and tools such as Decision Analysis, Simulation Modelling and Optimisation are covered to demonstrate the use of scientific methods in business decision making.

    Why National University of Singapore Business School?

    NUS Business School sits at the intersection of Asian markets and global management thinking in a way few schools can match. Its location in Singapore, one of the world's principal financial and trade hubs, gives executive participants direct access to Southeast Asian deal flows, regulatory environments, and corporate networks that are genuinely difficult to replicate anywhere else. The school's Asia-focused research depth, combined with strong ties to multinational corporations headquartered in the region, makes it a practical choice for leaders who need to operate across Asia-Pacific.

    Your Profile

    • The course is suitable for those who are interested in business analytics without any prior knowledge. Specifically, the course assumes that participants are new to the Analytics field without any programming and probability concepts, and will introduce Microsoft Excel to them as the main computing software.
    • Participants will be required to bring their laptops to class, and to analyse data in class using Excel Spreadsheets. This course assumes a very basic level of comfort with Microsoft Excel: ability to import data, sort it, and perform simple functions such as addition, multiplication, division, and creating tables.

    Benefits

    • Use Excel formulae, Pivot Tables, and charts to summarize and stratify business data.
    • Apply decision trees and probability analysis to make structured decisions under uncertainty.
    • Run simulation models in Excel to assess risk and analyse complex business scenarios.
    • Formulate and solve linear and discrete optimization problems using Excel Solver.

    What You'll Learn

    • Online Session 1 - Data Intelligence to summarize data: use Excel formulae and cell referencing; conduct basic summary of data.
    • Online Session 2 - Pivot Table analysis: use Pivot Tables in Excel to stratify data; use Pivot Charts to visualize data.
    • Online Session 3 - Foundation of Decision Making under Uncertainty I: compute conditional probabilities; understand and use Bayes' rule.
    • Online Session 4 - Foundation of Decision Making under Uncertainty II: concepts of random variables; differentiate between discrete and continuous probability distributions.
    • Online Session 5 - Introduction to Simulation Modelling: use Excel to simulate a variety of random variables; carry out simulation to analyse business decision problems.
    • Online Session 6 - Decision Trees: illustrate a decision tree and its power in decision making; use decision tree to make business decisions under uncertainty.
    • Online Session 7 - Introduction to Linear Optimization: formulate a Linear Programming (LP) mathematical model; solve the optimal solution of an LP using Excel solver.
    • Online Session 8 - Introduction to Discrete Optimization: construct binary constraints; logical constraint formulation; big-M notation; review and assessment.

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