Business Intelligence & Analytics (BI&A), formerly known as Institutional Research and Analytics Unit (
BI&A provides training to faculty and staff to build up the University’s analytics capability.
It aims to:
- Develop a reporting platform to facilitate information sharing and decision making
- Perform or assist in analytics projects
- Work with other SUSS units to deploy project findings
In addition to the above, BI&A collaborates with other internal SUSS units (as well as faculty and staff) to formulate and implement analytics projects, and provides ad hoc advice. Such collaborations provide opportunities for training and learning.
More recently, BI&A has started to collaborate with external organisations on learning analytics projects. Besides contributing to the community, SUSS hopes to share its analytics expertise and experience with external organisations with a view to
One of BI&A’s major roles is to build up the analytics capability in and of the University. This, in turn, requires training to be a core part of what BI&A does. The data mining/analytics training provided by BI&A was first implemented in November 2016. It comprises seminars, computer sessions, consultations and coaching, and collaborative projects.
Dashboard training for SUSS faculty and staff has been implemented. The scenario-based sessions provide participants with the opportunity to learn the fundamentals required for self-service visualisation and discovery using data visualisation tools.
Consultations and Coaching
As part of its training as well as to facilitate the implementation of analytics projects in SUSS, BI&A provides consultations and coaching on an ad hoc basis. This initiative is available to the faculty and staff of the University. As and when necessary, consultation and coaching will also be offered to staff from external organisations.
The analytics project team is responsible for developing and implementing university-wide analytics (including BI) projects and other SUSS unit-specific analytics projects.
The Data Warehouse (DW) collects SUSS data, sourced from applications such as SIMS that allows users to generate information and insights for decision making. The Data Warehouse is currently developed to house historical data. It will also provide point-in-time snapshots to support users in their data needs.