Singapore University of Social Sciences

Data Strategy and IoT Business Models

Data Strategy and IoT Business Models (AIT505)


Almost every organization has the buy-in from its senior management for carrying out AI and IoT projects for enhancing the business. However. AI and IoT is not mere collection of data and storing them in archives. The IoT projects must not be like adding sensors, retrieving the data and displaying them to the stakeholders as value-add. The IoT projects must be properly and carefully designed to capture and deliver long-term innovative and differentiated value. Thus a proper data strategy and use of appropriate IoT business model is crucial. This course introduces data strategy, challenges in data integration and the IoT business models.

Level: 5
Credit Units: 5
Presentation Pattern: EVERY JULY


  • IoT data capture and management
  • Data volume, complexity, security and privacy
  • IoT Business Model
  • IoT product development and monetization
  • Subscription-based model
  • Outcome-based model
  • Asset sharing model
  • Asset tracking model
  • Compliance model
  • Data-driven model
  • Razorblade model
  • Pay-per-usage model

Learning Outcome

  • Discuss the methods available for capturing data.
  • Examine the complexity and volume of data that can be generated by an IoT system.
  • Compare the different business models available to monetize the proposed IoT solution.
  • Recommend appropriate business models for the proposed IoT system.
  • Plan a strategy for data capture and management.
  • Appraise the resources required for the IoT solution.
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