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Saviant Student Analytics Platform (SSAP)

SSAP helps to intelligently manage your students’ academics, predict drop out probability and define additional learning assistance models using your student data. Empower your Educational institution with our Analytics solution and facilitate intelligent initiatives & insights.

Saviant’s Student Analytics solution helps you to empower your educational institution practices with analytical capabilities and improve overall experience for your students. With this solution, you can ingest the student’s data to identify his/her performance gaps. You can get a unified view of the student’s KPIs such as assessment scores, attendance records and grades to identify the underperforming areas.

Our analytical expertise has helped create student analytics solution that can help you identify students who are likely to drop out or disengage. Thus, it enables the ability to intervene potential dropout students at an early stage in order to improve the overall graduation rate.

This solution addresses several scenarios such as academic intelligence, predictive models and advanced analytics for student performance improvement, smart campus initiatives, and insights on student attendance.

Solution Benefits:

  • Derives alerts and notifications on most important student KPIs.
  • Enables clear visibility of assessment scores, grades, attendance records and comparative analysis to identity drop out possibilities and more.
  • Derives potential drop-out student profiles and their academics’ strengths & weaknesses.
  • Synchronizes with your existing global educational data system for advanced analytics.
  • Provides critical insights on student’s attendance to track their active participation across classrooms, events and extra-curricular activities.
  • Saves thousands of dollars for institutions---- with this Cloud-based solution – as there’s no hardware and no software installation required.
  • Provides high-performance storage (less-than a second response time) and analytics of billions of data records.