Course overview

The rise of the big data analytics has fueled the need to make better use of this plethora and immense amount of data to drive decision making. All around the World, modern cities like the United States, Japan and Shanghai have endeavored to enhance the experience of living, working and playing in their home ground. Singapore is no exception: the public sector, together with the likes of banks, engineering firms, manufacturing companies, agricultural set-ups and many others from the private sector are also gaining grounds competitively through the adoption and use of big data analytics.

This 1-day course is specially designed for participants who are new to the space of big data analytics and its applications in the public and private sector. This workshop aims to equip participants with the relevant knowledge and appreciation of big data, where multiple case studies and used-case scenarios in this course will further enhanced understanding and learning for the participants.

Participants with no relevant training will find this course useful and enriching, while those who with some training or work experience find this course offering fresh insights.

Course benefits

Business Outcome

Participants will be equipped with the knowledge and concepts of big data analytics, what has been achieved by those riding this wave of big data, and how these can be adopted and applied in the various industrial verticals.

Learning Outcome

Participants will be able to:

  • Identify underlying trends and patterns in business data using statistical and computational techniques and tools
  • Develop, apply and evaluate algorithms, predictive data modelling and data visualisation to identify underlying trends and patterns in data

Course outline

Introduction and Overview

  • What is data science and big data analytics
  • Developments of data science and big data in the last few decades and recent years
  • How does it affect us and why we should be in the know

Principles of Big Data: Methods and Techniques 

  • Data Science Frameworks and Methodologies
    • A step-by-step guide to Big Data Analytics and how to harness the power of data to make effective business decisions
  • Understanding quantitative and qualitative data analysis methods
  • Understanding Business intelligence and Data Visualization
    • Descriptive Analytics: Reporting data graphically and address business issues with intelligence
  • Understanding business analytics, data mining and big data
    • Predictive Analytics: 
      • Primary predictive models
      • New models and developments in the space of predictive analytics
    • Prescriptive Analytics: What can we do about it
      • Data-driven insights and recommendations

Applied Big Data Analytics 

  • Case Studies and Examples involving applications of data analytics in solving business problem


1 day(s)

Who should attend?

(Level 2) Supervisors, Executive, & Emerging Managers     
(Level 3) New Managers     
(Level 4) Managers

Programme leader

Mr Ng Jinsheng joined IBM SPSS in 2008 as an Executive in Training and Consulting after his graduation from the National University of Singapore (NUS) with a Degree in Statistics and Applied Probability. During his stay in IBM SPSS, he has trained hundreds of participants from the public service and private sector in statistical and data mining concepts, tools and applications in solving business problems. He has also led consulting projects and worked with C-level executives in addressing pressing business issues during which he received many praises and testimonies. During his working with IBM SPSS, Mr Ng also completed his Masters of Science in Knowledge Management [M.Sc(KM)] from the Nanyang Technological University (NTU) and graduated one of the top in his cohort with a Dean’s List award in academic excellence. He later joined SAS Institute as an Education Specialist in the Training department, and thereafter as a Senior Associate in professional Consulting services, where he won the “Excellence in Service” Award for founding and championing the inaugural Inter-Varsity Analytics Competition in 2014 (Singapore).

He is currently a founding member of his consultancy and lectures and trains at TertiaryI nstitutions in Singapore in the area of business statistics, data mining and big data analytics, and develops analytics courses for undergraduate programme sin Singapore. Professionally recognised by the Project Management Institute (PMI) as a Certified Associate in Project Management (CAPM), Mr Ng is also an IBM Business Analytics Certified Specialist in IBM SPSS Modeler (Professional)and IBM SPSS Statistics, as well as SAS Certified Predictive Modeler using SAS Enterprise Miner and SAS Certified Business Analyst using SAS 9: Regression and Modeling.

Course fee

Programme Fee Amount (including 7% GST) Remarks
Member Total Fee $749.00 -
Non-Member Total Fee $963.00 -
Early Bird Discount 10% Read Terms & Conditions

Programme Executive In Charge :Grace Tan

Telephone Number :62489414

Email : gracetan@sim.edu.sg

Non-members are welcome to sign up for SIM membership to enjoy the discounted rate.

To register for the programmes now, select the preferred programme run-dates below through the register icon.

Course runs

Date Time Venue Registration Closing Date Register
25-11-2021 to 25-11-2021 09:00 - 17:00 SIM MH 11-11-2021

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