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“I was looking for a reporting tool to help our senior managers and executives know the status of the major business processes with the ease of a mouse-click.”

Dr. Ahmed El-Haggan, VP of IT, CIO, & Prof of Computer Science
Coppin State University

 

HigherEd Analytics Application Metrics

Dimensional modeling had become a leading approach in data warehousing and is the foundation of our data model. We organize our data into subject areas. Some of our subject areas include:

  • Admissions
  • Student Term
  • Student Plan
  • Graduates
  • Registration
  • Class Schedule
  • Faculty Term
  • Student Financials

Some of the metrics we provide are directly mapped from ERP source data (e.g., Credit Hours Attempted), some are derived and stored in the relational fact tables (e.g., Admitted Count) and some are calculated in the OLAP engine at the aggregate level (e.g., Retention %). The value of the application is that the user doesn't have to calculate the metrics; they are calculated consistently and accurately for everyone within the application.

A sample of our metrics are shown below:

Admissions

  • Applicant Count
  • Pending Count
  • Admitted Count
  • Matriculated Count
  • Enrolled Count
  • % Admitted
  • % Admitted Enrolled
  • % Applicants Enrolled
  • Avg SAT Math Score
  • Avg SAT Total Score
  • Avg SAT Verbal Score

Student Term

  • Student Count
  • Enrolled Student Count
  • New Enrollee Count
  • Num Student Withdrawals
  • Prior Year Student Count
  • % Change in Student Count PY
  • Change in Student Count PY
  • Avg Credit Hours
  • Avg GPA Cumulative
  • Avg GPA Term
  • Avg Student GPA Change
  • Prior Term Cumulative
  • GPA Credit Hours Cum
  • Credit Hours Term
  • GPA Cum
  • GPA Term
  • Grade Points Cum
  • Grade Points Term
  • Cohort Retention %
  • Second Yr Retention %
  • Third Yr Retention %

Graduates

  • Degree Count
  • Graduate Count
  • Credit Hours
  • Average Credit Hours
  • Average GPA
  • Average Years to Graduate

Registration

  • Student Count
  • Enrolled Class Count
  • Registered Class Count
  • Drop Count
  • % Dropped
  • Credits Attempted
  • Credits Earned
  • Class Grade
  • Avg Class Grade
  • Avg Classes Per Student
  • Avg Credits Per Class
  • Avg Credits Per Student
  • Avg Enrollment Per Course
  • Avg Enrollment Per Section

Class Schedule/ Utilization

  • Num Courses Offered
  • Num Sections Offered
  • Avg Section Capacity
  • Avg Course Capacity
  • Avg Sections Per Course
  • Course Utilization %
  • Section Utilization %
  • Faculty Count
  • Student to Faculty Ratio

Faculty Term

  • Faculty Count
  • New Faculty Count
  • Years Employed
  • Average Years

The value of the application is that the user doesn't have to calculate the metrics; they are calculated consistently and accurately for everyone within the application.