Data Mining for Decision Making (CET105)

Dates: 6 November 2026
Venue: Singapore University of Social Sciences

Synopsis

Data mining is a very important tool that has helped to create new ideas and critical decision making in organisations, enterprises and government institutions. Data mining tools and techniques provide the right information for leaders so that the decisions taken might become positive realities. So how is data mining applied to strategic decision making?

This course provides an overview of data mining methodology and techniques, concepts and applications of association analysis, clustering and predictive modelling, and also presents the challenges and limitations of data mining.

Objective

A. Knowledge and Understanding (Theory Component)

By the end of this course, participants should be able to:

• Differentiate the various aspects of data mining
• Recommend data mining tools for association analysis, clustering and predictive modelling
• Discuss the use of data mining to support decision making
  
  

B. Key Skills (Practical Component)

By the end of this course, participants should be able to:

• Plan the process of data mining, i.e. CRISP-DM framework
• Execute techniques such as association analysis with Apriori, clustering with K-means, and classification with CHAID (Chi-Square Automatic Interaction Detection)
• Justify the use of appropriate data mining techniques for different business problems
• Interpret the results of a data mining analysis
• Evaluate the performance of data mining models
• Apply data mining using a software package, interpret the output, and recommend solutions for the problem(s) under consideration
  
  

Topics

Requirements

NIL

About the Trainer(s)

Dr Jess TAN is currently a Senior Faculty Lecturer in School of Business Unit at the Singapore University of Social Sciences. She is an analytics professional with more than 20 years of experience and a deep passion for data mining and its real-world applications. Published multiple papers on learning analytics in academic conferences and journals, with a recent contribution focused on volunteer management.

Extensive cross-industry experience spanning consultancy, telecommunications, banking, and entertainment. Previously served in the public sector as Head of the Business Intelligence & Analytics department, leading strategic data initiatives and driving insights for decision-making.

Application Procedures

Please submit the following documents to [email protected]:

1. Coloured copy (back and front) of NRIC for Singaporeans and PRs, or "Employment"/"S" Pass for foreign applicant
   
2. Application form
   
   

Course Fee

¹ Mid-Career Enhanced Subsidy: Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.
² Enhanced Training Support for SMEs: SME-sponsored employees (Singaporean Citizens and PRs) aged 21 and above may enjoy subsidies up to 90% of the course fees. 

• Participants are required to achieve at least 75% attendance and pass any prescribed examinations/assessments or submit any course/project work (if any) under the course requirement.
• Participants are required to complete all surveys and feedbacks related to the course.
• The course fees are reviewed annually and may be revised. The University reserves the right to adjust the course fees without prior notice.
• Singapore University of Social Sciences reserves the right to amend and/or revise the above schedule without prior notice.
  
  

For the various payment modes, please refer here.

Course Withdrawal and Refund

Request for withdrawal from a course must be submitted to SUSS Academy formally in writing.

• Course Withdrawal before Application Close Date: No charges.
• Course Withdrawal after course confirmation: 50% of the full course fee with an administration fee imposed.
• Course Withdrawal after the course commences: Full course fee applies.

For clarification, please contact the SUSS Academy via the following:

Telephone: +65 6330 9110
Email: [email protected]