Singapore University of Social Sciences

Data Visualisation and Analytics for Social Sector

Data Visualisation and Analytics for Social Sector (NPM513)

Applications Open: 01 May 2024

Applications Close: 15 June 2024

Next Available Intake: July 2024

Course Types: Modular Graduate Course

Language: English

Duration: 6 months

Fees: $2200 View More Details on Fees

Area of Interest: Management

Schemes: Alumni Continuing Education (ACE)

Funding: To be confirmed

School/Department: S R Nathan School of Human Development


NPM513 Data Visualisation and Analytics for Social Sector aims to discuss the use of data visualisation and dashboards, provide an overview of data mining and equip students with the knowledge of various applications of analytics for social good. The course covers the construction of charts and dashboards, dashboard design principles, data mining techniques (association, clustering and predictive modelling) and data mining applications such as recruitment of volunteers, engagement of donors and prevention of family violence.

Level: 5
Credit Units: 5
Presentation Pattern: Every semester


  • Data attributes
  • Charts appropriate for different types of data
  • Types of dashboards
  • Data preparation for data mining
  • Data mining methodology
  • Data mining techniques
  • Pre-requisites and limitations of data mining
  • Prospect identification
  • Volunteer segmentation
  • Targeted marketing
  • Churn modelling
  • Programme selection for re-offenders

Learning Outcome

  • Evaluate the appropriateness of Data Visualisation techniques based on given data.
  • Critique the design of the dashboard based on the design principles.
  • Examine the different modelling techniques used.
  • Assess the different data mining applications used.
  • Construct a dashboard using Tableau.
  • Recommend the appropriate analytics techniques for different business problems.
  • Evaluate the application of business analytics for social good.
  • Formulate possible applications of business analytics for social good.
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