Janice Hill, Columbus State University
- Define KPI’s : grades, starting degree, ending degree, and many more.
- Design and Implement : ODI integrator
- Subject area example : summation helps reports only pull one row per student.
- Updating : degrees awarded only loaded at end of term.
- Validation of data : Work with Institutional Research to figure out where wrong. Consulting with individuals who think data did not look right.
- Production release : Start a new cycle.
- Data elements:
- Banner, PeopleSoft, Excel spreadsheets
- student head count, student attempted credit hours, and about 30 others.
- Dashboards : 8 in production, 2 in completed validation, 2 subject areas ready to be built. Changes to a dashboard not saved across sessions, so users need to export to a file.
- Structure of Dashboard : Level prompts : College, department, program, major, term. Analysis. Footnotes.
- Users with access : President, VP, Deans, Dept heads.
- Export types : PDF, Excel, Web,
- Errors: BI data loaded at 6am, so local data pulled at 9am WILL result in very small differences.
- Progression dashboard : credit hours by term, avg GPA by class, avg GPA vs credit hours earned, demographic breakdowns, grades by academic level, grades by section
- Retention and Graduation dashboard : after 1 year, after 6 years. Use both counts and percentages.
- Talk with faculty about their data needs so can show it exists or build it into a report.
- Individualized training. Understanding how to filter is a challenging concept.
- User tracking enabled, so know how long they stay on a dashboard, filters used, the SQL used.
- Try to use as little filters as possible. Her job to get the data. User’s job is to interpret.
- Decisions and policy affected by this data.
- Trying to get grade data to improve early warning.
- What are the products for which they want analytics?
- Using University System of Georgia requirements for retention, so pegged to Fall enrollment. “Some times you have to go past what makes sense to you and implement the rule.”