Data Sources

1. HEMIS Data Warehouse
2. ITS Views Data Warehouse
3. PeopleSoft Data Warehouse
4. Peer Data Warehouse
5. Research Data Warehouse

Reporting

6. PowerHEDA

Higher Education Modules

7. Funding Allocation Model
8. Business Plan Generator
9. Enrolment Planning
10. HEMIS Manager
11. Student Tracking
12. Student Application Ranking System
13. Annual Performance Plan Monitor
14. Viability
15. Workload & Staff Time Sheets
16. Research Information Module

Higher Education Services

17. Learner Analytics & Predictive modelling
18. Resource Allocation modelling
19. Space modelling & scenario analyses

All PowerHEDA Dashboards represent data from a secure, flexible data warehouse. The data in the PowerHEDA Warehouse is imported from various sources, including operational data sources and Excel spreadsheets that can be used in conjunction with the HEMIS and Enrichment Data.

The PowerHEDA Portal Layer is the only compulsory module and consists of five core components:

• Data Component, which includes:
  • Relational and OLAP databases
  • HEMIS Data (per calendar year and submission)
  • Enrichment data tables (the value add institutional data)
  • Data import procedures
  • Datasets
  • Integrated business logic
• Security Component – a role-based design
• Web Portal in the form of a dashboard
• Administrative functions
• Online help and training resources

The PowerHEDA REPORTING layer focuses on different kinds of reports designed to answer the question: “What happened?”. These reports are provided using the DHET Higher Education Management Information System (HEMIS) data or operational data within the Institution. Reporting is done at strategic and/or operational levels.

• The Cube Report Viewer module provides multi-dimensional reports to assist with detailed student or staff related information and this module enhances the ad hoc reporting process at institutions.
• The HEMIS Management Reporting module is also available to assist institutions with reports at various levels in relation to HEMIS data.
• The Dashboard module provides a visual display of key performance indicators and metrics on a single interactive screen.

The Cube Report Viewer module is a powerful multi-dimensional tool that empowers the user to view, interrogate and report on data quickly without compromising data integrity and accuracy.

Key features of the Cube Report Viewer module include:

• Build cube solutions
• A choice of three different viewers
• Export any view of your data
• Slice and dice your cube for true multi-dimensional views
• Drag and drop dimensions and manipulate your cube views

The HEMIS Management Reports module are dynamic, interactive reports, giving the user the power to select exactly the report criteria that is required. All reports are set up with the option to print if required.

Key features of the HEMIS Management Reports module include:

• Use report templates for rapid report development
• Select the layout of your static report
• Create summary and list reports
• Export your data for further manipulation
• Parameter-driven reports so that you don’t have to create multiple reports
• Online link to help and training resources
• Schedule function to run reports at your convenience

PowerHEDA uses Dashboards to display graphs, data and indicators in a user-friendly manner

Key features of the Dashboards module include:

• Fully customisable layouts and formatting
• Integrated data filters at a dataset, report or dashboard level
• Interactive chart and drillable table widgets to display your data
• Spark-line graphs at row level to give the visual effect for data comparison
• Visual display of Key Performance Indicators (KPI’s) with detail tooltips
• Link to other PowerHEDA objects including Cube Reports, Management Reports, Documents, Applications and other Dashboards
• Export a snapshot image of your dashboard or any widget

The PowerHEDA ANALYSIS layer focuses on the evaluation of data in different forms to answer the question “Why did it happen?”. Within this component, there are four PowerHEDA Modules.

• The Application Requirement System (ARS) module evaluates key student information prior to applying to the university in order for the university to select the students qualifying for a particular qualification.
• The Student Cohort module focuses on the evaluation of activities of a particular student cohort over time and determines the student retention trends at different levels.
• The Viability modules assess the financial risk of the university/faculty/department/academic programme or academic module.
• The Resource Allocation Module (RAM) evaluates the different resources of a university and develops scenarios for the fair distribution of resources at different levels within the university.

Key features of the Application Requirement System module include:

• Database version of Prospectus with user friendly setup of programme criteria
• Integrate with NSC Matric results
• Apply criteria and rank students
• Parameter driven reports with on the fly adjustment of criteria

Key features of the Student Cohort Analyses module include:

• Track a predefined cohort of students
• Measure the cohort reliably and consistently
• Management and programme overview
• Student Cohort Analyses uses a proven, established methodology to ensure accuracy
• User-friendly reports and dashboards

Key features of the Viability module include:

• Setup of reporting and academic structures
• Safe and secure environment for financial risk analysis
• Setup of distribution methodology through data drivers
• Combine staff, student, finance and research data
• User-friendly reporting

Key features of the e Resource Allocation Model (RAM) module include:

• Create Income Projection models
• Apply long term planning based on targets and norms
• Analyse academic and support divisions

The PowerHEDA MONITORING layer focuses on monitoring annual performance in relation to staff, students and university planning to answer the question “What is happening?”

• The Annual Performance Plan Module (APPM) monitors and reports on the progress made in relation to the strategic plan of a University, Faculty or Department/School/Division.
• Interrogator Pro and Audit modules assists a university in monitoring the data quality and management processes in order to rectify incorrect data elements
• The Student Tracker module assists an institution in monitoring the academic progress of students within academic programmes or modules.
• The monitoring of activities of academic staff members and the monitoring of time management of academic staff in relation to Teaching and Learning, Research, Community engagement and administrative duties are provided with the Staff Time Sheets and Workload module.
• The monitoring of available and required space in line with the enrolment plan is the basis of the Space modelling service

Key features of the Annual Performance Plan module include:

• Create multiple plans
• Target setting for multiple milestones
• Take snapshots to record a point in time
• Add multiple activities and costing per resource at any level
• Assign and evaluate responsibilities at any level
• Integrate PowerHEDA KPIs into any plan
• Dynamic reporting on any plan

Key features of the Interrogator Pro module include:

• Upload HEMIS data to a secure environment
• Automated error queries on VALPAC
• User-defined error report distribution setup
• Email notification of Excel error report to data owners

Key features of the Audit Applications module include:

• Dynamic setup of audit profiles
• Secure environment for data handling
• Auditable change log
• Upload attachments and add comments
• Take snapshots to record data at a point in time
• Make change requests
• Monitor through audit statuses
• Detail report of requested changes

Key features of the Student Tracker module include:

• Identify multiple risk
• Personalise a custom e-mail template
• Upload attachments
• Secure environment for data handling
• Notification via e-mail or bulk sms file

Key features of the Staff Time Sheets and Workload module include:

• Link time table, student, staff and research data
• Use templates for uniform recording
• Apply institutional guidelines
• Secure environment for data handling
• Processes driven by status
• Capture additional related data if required
• Create HEMIS Time Sheet Data from Workload

Key features of the Space Modelling Service include:

• Link enrolment plan and space data
• Load space norms to the required detail
• Compare actuals with current requirements
• Compare current with panned requirements
• Observe financial implications

The PowerHEDA PREDICTION layer focuses on forecasting and predicting the future in relation to funding, academic programmes, student enrolments and student retention by answering the question “What might happen?”. There are three PowerHEDA modules and a service that is provided within this component.

• Predicting the income and student statistics in relation to the offering of new academic qualifications are provided within the Business Plan Generator module
• The annual subsidy received from the Department of Higher Education and Training (DHET) is forecasted using the Funding Allocation Model (FAM).
• The submission of student enrolment plans to the Department of Higher Education and Training (DHET) is performed using the Student Enrolment Planning module. This module also assists in regular monitoring of the agreed-upon student enrolment targets.
• Predictive Learner Analytics is a statistical service provided by IDSC to determine the probabilities of students at risk and generate a list of student names with contact details.

Key features of the e Business Plan Generator module include:

• Generate new programmes for consideration
• Parameter driven with actual institutional guidelines
• Financial Rand-value prediction
• Apply space norms
• Calculate income and expenditure
• One page management overview report
• Integrate with enrolment planning

Key features of the Funding Allocation Model (FAM) module include:

• Automatically incorporate Ministerial Statement changes
• Build and compare scenarios
• Import HEMIS data
• Capture research data
• Calculate block grants
• Distribute to academic levels

Key features of the Student Enrolment Planning module include:

• Apply default growth parameters
• Use historical trends for predictions
• Override parameters
• Qualification and offering type level
• Evaluate new qualifications
• Incorporate DHET Tables
• Monitor and evaluate the planned models against actual results

Key features of the Predictive Learner Analytics service include:

• Identify at-risk programmes
• Extract student data and populate the KNIME model
• Generate probability output
• Import probability output in PowerHEDA
• Detail reporting on student level

One of the biggest needs regarding benchmarking in the higher education sector is the availability of reliable data. IDSC is a private South African company that developed the web-based Peer Data Sharing (PDS) application to help address the above. A conscious decision was made to use HEMIS data for this data sharing project which enables an institution to compare itself with a selection of Peers on certain indicators.

IDSC developed this reporting function and will continue to maintain the PDS reports.

SATN

An enhancement of the PDS application were requested by the South African Technology Network (SATN), which provides a flexible tool for comparing aggregated data of the 23 institutions, for the years 2000 to 2007.

The enhanced PDS was commissioned by the SATN Performance Indicators Project and implemented by IDSC, developers of higher education MIS software.

The application allows a user to cluster institutions into groups for purposes of comparison. Data is then extracted for a particular indicator (or type of data) and the result displayed in a line or bar chart.

Up to seven different groupings can be specified by the user. An initial set of 17 indicators is provided. The data used in the graphs is also accessible in tabular form.

The data extracted by the PDS application is from HEMIS, the DHET Higher Education Management Information System. The final, audited submissions of data from the institutions are used, at an aggregated level, as supplied by the DHET.

The new enhancement has been developed as part of the 2008 SATN Performance Indicators Project, to which Universities of Technology and Comprehensive Universities have contributed.

Research Data

An improvement to the PDS web site occurred during May 2009 with the introduction of research related data and also an additional reporting functionality (Indicator Explorer) with the assistance of North West University.

This Research related data includes Research Publications, Research Block Grant Funding, and the Number of Rated Researchers in the Higher Education Sector.

HEMIS data

The HEMIS data set is annually provided by the Department of Higher Education and Training (DHET), based on the following process. Second HEMIS submission data (Year N) will be available at the end of May (Year N+1) and final audited HEMIS submission data (Year N) will be available from August (Year N+1).

The August data submission will also include any resubmitted data of previous years. It is important to note that the May submission is provisional and possibly incomplete data.