How We Data – UNIVERSITY ANALYTICS AND INSTITUTIONAL REPORTING

The University of Utah has a wealth of data about its students, faculty, staff, financials and other topics covering the breadth of its resources and operations. These data elements are a vital asset used by University leadership, state, and federal governing bodies to inform decisions about university programs, initiatives, budgets and operations.

The Office of Budget and Institutional Analysis (OBIA) is charged with bringing data together from multiple operational areas on campus to analyze and generate insights. We generate official information for University leadership, the Utah System of Higher Education (USHE), the U.S. Department of Education (IPEDS) and other external audiences. In addition, we provide ad hoc support to University divisions for a variety of data needs and dedicated analytics for partner colleges.

We coordinate with several offices on campus to understand the data they generate, improve data quality, and integrate the data into an institutional-level view of our academic resources and student outcomes.

Data Sources

Methods

Student Data

Faculty & Staff Data

OBIA’s REPORTING DATABASE

This is used to generate official numbers reported to state and federal governing bodies and other aggregate reporting when requirements dictate data should align with official figures. Data is extracted from PeopleSoft and other source systems, checked for quality, and transformed into new structures that facilitate reporting. We enhance the data with standard definitions that meet external agency reporting guidelines and allow baseline comparisons between the University of Utah and peer institutions, and incorporate internal definitions that support institution-wide assessment and planning.

Data Timeframe

Data is constantly changing in PeopleSoft and other U of U systems, with updates and corrections hitting the system real-time. When data is pulled directly from PeopleSoft it can reflect up-to-the-minute state of the data.

OBIA’s reporting database will always lag behind PeopleSoft data. While some of our processes use data that is updated as often as nightly, much of our reporting is based on data feeds that occur a few times a year on designated dates. Some of the reasons for this are:

USHE, IPEDS and other agency surveys require us to capture and freeze reported data at specified points within the academic year to allow a baseline comparison with other higher education institutions when they reach the same point of time in their academic year.
It facilitates year-over-year benchmarking.
It allows time to research and resolve source data issues before data snapshots are taken.

Data we report will reflect one of the following types of timeframes:

Current: Up-to-date data, generally refreshed nightly.
Snapshot Date: Data as-of a specified point-in-time and then frozen (updates and corrections are generally not applied until the next snapshot is taken). For example, we will capture a student’s declared major at the beginning of the semester, and again at the end, but if they change their declaration multiple times mid-semester, we will not capture each change.
Time Period: data that accumulates or applies to a period of time, such as a grade for a class earned over the course of a term, a financial aid award for an academic year, employee earnings in a pay period, etc.

Data Level

When we report aggregate figures such as headcount and full-time equivalency, we must choose the level at which to aggregate. Different levels will deliver different numbers.

For example, if a student declares two majors, one within the School of Business, and one within the College of Social & Behavioral Science, each of these colleges might include the student in their internal headcounts. If we were to add the total headcount reported by each college to arrive at the number of students at the university as a whole, this student would be counted twice in error:

To prevent this, we apply rules to select just one major as the students’ primary, then only include primary major in the university-level student headcount:

OBIA generates official figures at the university-level, even when providing drill down by college, department, major, and others. In the example above, OBIA would count the student in the Accounting major, and not include him/her in the Criminology major headcount.

Data Level

Official student data is reported at the university-level. Students are counted once per student career; that is, if a student is pursuing both an undergraduate and graduate level degree at the same time, they will be counted once within each career. However, if they are pursuing two undergraduate degrees at the same time, they will only be counted once overall, under the major identified as their primary major.

OBIA does support student reporting at other levels when requirements dictate, and will indicate when we do so in the report documentation.

Data Level

Official faculty counts are generated at the university-level, as follows:

Each faculty member is counted only once, under the position identified as their primary position
Only regular faculty positions are included, with a few exceptions: some tenure and career-line faculty and instructors of credit-bearing classes are included when their primary position is supplemental.

Official staff counts are provided by Human Resources, not OBIA, but OBIA does report staff counts to several agencies following the same rules we apply to faculty counts

Data Definitions

Position: A job title held by an individual in a given Org. Employees may have multiple jobs (employment record numbers) in PeopleSoft that roll up to a single position.
Regular vs Supplemental: We flag jobs as supplemental when they are temporary, unpaid, or assigned to a non-employee job title or Org such as volunteer faculty, phased and early retirees. All others jobs are considered regular. With few exceptions, only include regular positions are included in our reports.
Full-time vs Part-time: We take the sum fte of Regular jobs (omitting supplemental fte’s) to determine full or part-time status. Sum 0.75 or greater is considered full-time, with the exception of Graduate Assistants who are always counted as part-time.
Primary Position: Employees can hold multiple positions at a time, but only one will be selected as their primary, selected in this order of priority:
1. Regular jobs are chosen over supplemental jobs. Paid supplemental jobs are selected over unpaid.
2. Position in which the employee spends the majority of their time.
3. Position with the highest salary grade
4. Position with the highest academic appointment rank
5. Position in the faculty members tenure home department
6. Position in the employment home department
University Administration: Consists of the University President, Senior VP’s, VP’s and College Deans.
Faculty: employees are counted in the following faculty categories when their primary position meets the following:
- Tenure-Line Faculty: includes both faculty administrators (those with tenure-line appointments that are serving in top University Administration) and those with an active, tenure-line job, whether paid or unpaid.
- Librarians: those with an active tenure-line librarian job, whether paid or unpaid.
- Military Sciences Faculty: those with an active tenure-line job in a Military Sciences division.
- Career-Line: those with an active career-line job that is paid.
- Visiting and Adjunct: those with an active visiting or adjunct job that is paid and is teaching a for-credit course.
Primary Academic Appointment: The appointment with the highest category and rank, selected in this order:
1. Faculty Category
  1. Emeritus
  2. Tenured
  3. Tenure-track
  4. Career-Line
  5. Visiting
  6. Adjunct
2. Faculty Rank
  1. Professor
  2. Associate Professor
  3. Assistant Professor
  4. Instructor

UNIVERSITY ANALYTICS AND INSTITUTIONAL REPORTING

PEOPLESOFT

OBIA’s REPORTING DATABASE

STUDENT DATA WAREHOUSE

Data Timeframe

Data Level

Data Level

Data Level

Data Definitions