Text Mining and Big Data for Decision Making (CET106)

Course ID: TGS-2023020761
Dates: 6 May 2026, 5 August 2026
Level: Basic
Venue: Singapore University of Social Sciences

Synopsis

We are in the midst of a data explosion that is creating unique challenges and opportunities for organizations. Unless data can help decision makers make better decisions, enhance strategic initiatives, better communicate with consumers, better allocate resources, there is little value to this resource, big or otherwise.

This course discusses the use of text mining and Big Data in decision making. Topics include text mining terminology and hierarchy, challenges in dealing with text, text mining process and applications, overview of Big Data, various Big Data analytics techniques and challenges of Big Data.

Who Should Attend

Business professionals, Marketing professionals, Data analysts, Other professionals who need to learn how to handle big data.  

Topics

• Text mining
• Text mining technologies
• Big data
• Big data handling and methods.

Learning Outcomes

A. Knowledge and Understanding (Theory Component)

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

• Define text mining and its process
• Explain the hierarchy in text mining terminology
• Outline the challenges in dealing with text
• Define the characteristics of Big Data
• Explain the potential benefits and challenges of using Big Data
• State the differences between Hadoop and the traditional databases in supporting Big Data
• List the various Big Data analytics techniques
• Discuss the challenges of Big Data
  
  

B. Key Skills (Practical Component)

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

• Recommend the appropriate analytics techniques to generate useful information to support decision-making for a variety of business and other problems
  
  

Schedule

Assessment

• Online Test

Requirements

• Minimum qualification of diploma.

Trainer's Profile

Dr. Zhang Yimiao is currently the Deputy Head of Business Analytics Programme at the Singapore University of Social Sciences. She has been teaching different text mining and data mining courses in the Business Analytics Programme. Her main research interests are focused on text mining and data mining in social media, e-commerce, and blockchain-based applications.

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 6248 0263
Email: [email protected]