In our last blog entry, we worked through the identification of a pair of KPIs (Student Enrollment and Student Retention) and a set of measures related to Student Enrollment. The next step is identifying the dimensions. As we mentioned earlier, a dimension provides a means to view data elements that categorize the measures. In Data Warehousing design, dimensions contribute to a multidimensional view. The more dimensions, the greater the degree of data complexity. A multidimensional view enables you to slice and dice the data in many dimensions.

To help you define the dimensions associated with the measures identified above, you need to ask more questions! How do you want to view the enrollment trend? By Gender? Ethnicity? Academic Program? Term? Academic Year?

Here are some sample Dimensions you may use to view your data:

1. Gender – enables you to view enrollment by Female or Male head count
2. Ethnicity – enables you to view enrollment by ethnic group (African-American, Asian, Hispanic, etc.)
3. Academic Program – enables you to view enrollment by programs in which students are enrolled
4. Term – enables you to view enrollment by summer, fall and spring terms

Through our exercises, you have definitely laid the groundwork for identifying KPIs, measures and dimensions associated with your institution’s strategic goals.

The table below shows the high-level matrix of KPIs, measures and dimensions:

In our next blog entry, we will explain the use of digital dashboards to display the data represented in the tabular graphic above.

Tags: BI, business intelligence, Data Warehousing, Higher Education, Key Performance Indicators, KPI, student administration

This entry was posted on Friday, October 9th, 2009 at 2:07 pm and is filed under business intelligence. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.