Course Description:
An advanced exploration of Business Intelligence tailored for the African enterprise landscape. Focuses on resource-optimized architectures, mobile-first design, and regional industry applications (AgriTech, FinTech/Mobile Money, Telecom, and Supply Chain). This course advances students beyond traditional reporting into modern, cloud-native, and AI-driven Business Intelligence. It focuses on architecting scalable data systems, embedding predictive and generative AI into decision workflows, and governing data ethically within the Kenyan and East African regulatory framework.
Course Learning Outcomes (CLOs): By the end of this course, students will be able to:
1. Architect cost-effective, cloud-native data lake-houses and semantic layers for enterprise scalability.
2. Integrate AutoML and Generative AI agents into BI workflows to enable predictive and conversational analytics.
3. Design real-time, event-driven streaming pipelines for operational intelligence in high-volume sectors (e.g., FinTech, Logistics).
4. Apply cognitive design principles to create mobile-first, embedded dashboards tailored for low-bandwidth environments.
5. Implement robust data governance frameworks compliant with the Kenya Data Protection Act (2019) and mitigate algorithmic bias.
6. Lead an enterprise BI transformation project, calculating ROI and managing organizational change.
Netiquette Guidelines:
Professional conduct for peer discussions and industry partner communications during the Capstone Project.
An advanced exploration of Business Intelligence tailored for the African enterprise landscape. Focuses on resource-optimized architectures, mobile-first design, and regional industry applications (AgriTech, FinTech/Mobile Money, Telecom, and Supply Chain). This course advances students beyond traditional reporting into modern, cloud-native, and AI-driven Business Intelligence. It focuses on architecting scalable data systems, embedding predictive and generative AI into decision workflows, and governing data ethically within the Kenyan and East African regulatory framework.
Course Learning Outcomes (CLOs): By the end of this course, students will be able to:
1. Architect cost-effective, cloud-native data lake-houses and semantic layers for enterprise scalability.
2. Integrate AutoML and Generative AI agents into BI workflows to enable predictive and conversational analytics.
3. Design real-time, event-driven streaming pipelines for operational intelligence in high-volume sectors (e.g., FinTech, Logistics).
4. Apply cognitive design principles to create mobile-first, embedded dashboards tailored for low-bandwidth environments.
5. Implement robust data governance frameworks compliant with the Kenya Data Protection Act (2019) and mitigate algorithmic bias.
6. Lead an enterprise BI transformation project, calculating ROI and managing organizational change.
Netiquette Guidelines:
Professional conduct for peer discussions and industry partner communications during the Capstone Project.
- Don/Lecturer: DON CHARLES NJENGAH