Data-driven cohort trend
and attrition analysis.
Cloud-powered dashboards analysing student cohort trends, attrition, and completion — surfacing early-risk students for targeted intervention and supporting timetabling and resource planning.
Fragmented data hid the cohort signals that mattered.
Limited ability to analyse cohort trends due to fragmented data. Early-risk students were difficult to identify, hampering proactive intervention and limiting the data-driven planning needed for timetabling and resource decisions.
Unified cohort data with cloud-powered models and dashboards.
Built dashboards analysing student cohort trends, attrition, and completion using cloud-powered data models — making cohort progression and risk visible by programme, intake, and equity group.
Unified cohort data model
Brought fragmented enrolment, withdrawal, and progression data into a single cloud data warehouse model.
Cohort progression dashboards
Power BI views show attrition and completion by program, intake, and equity group — enabling targeted intervention.
Early-risk flagging
Agreed rules surface at-risk students so advisors can act sooner — moving from reactive to proactive support.
Headcount & load views
Live enrolment and load data underpin timetabling and resource planning across all faculties.
Cohort insight at the speed of decision.
Cloud data warehouse models student journey events into cohort-shaped facts; Power BI exposes progression, attrition, and early-risk indicators to advisors and faculty leadership.
Cohort signals translated into action.
Student retention
Targeted, data-driven interventions across program, intake, and equity group.
Earlier risk detection
Advisors act sooner — using agreed rules to flag students before disengagement embeds.
Live progression view
Enrolment and withdrawal changes reflected quickly in the dashboard.
Planning-ready
Headcount and load views support timetabling and resource planning across faculties.