Interactive Academic Performance Analytics Dashboard for Universities

Design and develop an interactive data visualization system to analyze student academic performance across departments, semesters, and subjects. The system should help administrators and faculty identify performance trends, at-risk students, and subject-wise analytics through dynamic dashboards and predictive visual insights.

Collect academic datasets including marks, attendance, demographics, and course details.

Clean and preprocess data using Python (Pandas) or R.

Design a relational database schema to store structured academic data.

Implement backend APIs for data retrieval and aggregation.

Develop interactive dashboards using Power BI/Tableau/Plotly/D3.js.

Create visualizations such as heatmaps, bar charts, trend lines, GPA distributions, and attendance-performance correlation graphs.

Implement filtering options by department, semester, gender, and subject.

Add predictive visualization for identifying at-risk students using regression or classification models.

Integrate drill-down functionality from university level to individual student level.

Ensure responsive web-based interface for multiple devices.

Conduct usability testing with faculty members.

Document system architecture, visualization techniques, and user guide.

Present analytical findings and insights derived from the visualization system.