Overview
Data literacy training for UW–Madison faculty, staff, and students to find, interpret, and evaluate institutional data.
Learning Objectives
- Gain an understanding of the UW–Madison institutional data landscape
- Identify critical skills needed to evaluate and interpret data
- Understand various access controls and authorization requirements
Institutional data landscape
The university maintains hundreds of databases and systems that house institutional data. Any system holding institutional data shall be purposefully planned, inventoried, and implemented to manage institutional data throughout the entire data lifecycle in compliance with all applicable laws; Board of Regents, UW System Administration, and university policies, procedures, and standards; and approved records schedules.
System(s) of record, also known as source systems, are the single system deemed to be the university’s authoritative instance of a particular data element. Examples at UW Madison include the Student Information System (SIS), the Shared Financial System (SFS), and the Human Resource System (HRS).
Ancillary systems source their institutional data from systems of record. However, to the extent possible, unnecessary duplication or storage of institutional data should be avoided and university standards for integrations shall be followed such as using APIs or tools such as Person Hub.
Data warehouses and data lakes combine data from multiple sources for analytics purposes. UW–Madison data warehouses extracts data from enterprise source systems. Read more about UW Madison enterprise data warehouses: InfoAccess and Badger Data and Analytics Platform.
Popular UW–Madison Data Systems
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Student Information System (SIS)
The Student Information System (SIS) is an Oracle/PeopleSoft product which serves as the enterprise-wide transactional software that houses student data. It is the infrastructure of UW–Madison’s student administrative services (e.g., admissions, financial aid, student financials, course, and student data). SIS has limited querying and reporting capabilities.
Data Center is a tool within SIS which expands its student and curricular reporting capabilities. Data Center is primarily useful to create lists of students who meet specific user-defined curricular or academic criteria.
Advising Gateway
The Advising Gateway provides a single point of access to student record information for advisors. The Advising Gateway is available through the Advising Tools Catalog.
Degree Audit Reporting System (DARS)
The Degree Audit Reporting System (DARS) is used by advisors and departmental staff to audit the progress of most undergraduate degree programs and certificates to advise their students for registration. Additionally, students can use this tool to see which degree requirements must still be fulfilled.
HR Systems
HR Systems are listed on this page and include tools to access HR, payroll, and benefits data and reporting.
Update With UW’s Administration Transformation Program (ATP), Workday will be implemented as a replacement for the current HRS on July 1, 2025.
Universities of Wisconsin System Data Warehouses
WISDM / WISER: access to data from the Shared Financial System (SFS).
EPM: access to data from the Human Resource System (HRS).
NOTE: Workday replacement scheduled July 2025, read more about the Administrative Transformation Program (ATP)
Finding data
Data discovery tools include catalogs (where datasets are described but not stored) and repositories (where data are described and stored) or a combination of multiple sources known as aggregators.
UW–Madison Data Catalogs
- RADAR: The UW–Madison data catalog for institutional data sources, interactive data reports, and data visualizations (e.g., Tableau dashboards).
- Data Digest: Annual overview of trends in the students, faculty and budget of the university provided by DAPIR.
Global data catalogs and repositories
- Worldwide government data: http://data.un.org
- US government data: http://data.gov
- State and city data (search for your local civic data repository)
- Wikidata: https://www.wikidata.org
- Google Dataset Search: https://datasetsearch.research.google.com/
- International index of data repositories: http://re3data.org
- DataCite Commons: https://commons.datacite.org
Understanding and evaluating data fitness for purpose
General things to ask yourself when understanding and evaluating data for use:
- Why was this data collected?
- How was this data collected and managed over its lifecycle?
- Who performed the data collection?
- What quality control measures were in place during data collection?
- What data is included in this sample (e.g., raw or processed? aggregated sample? limited sample?)? Was any data removed and why?
- If data was collected from individuals, who is represented in this sample and who may be missing?
- What documentation and metadata exists to understand the data collection process (e.g., survey instrument used, detailed processing notes, reproducible analysis protocol)?
- Under what conditions may I reuse this data?
Access to UW–Madison institutional data
Access to protected institutional data (e.g., data not released publicly) is strictly managed. Access is granted by an appropriate data steward following the process outlined in the UW–Madison Institutional Data Access and Authorization Standard (March 1, 2021).
Tip: Learn more about how to request access to institutional data dashboards and reports.
Acknowledgement of Responsibilities for Sensitive and Restricted Data
As an individual authorized to access sensitive or restricted institutional data, you must take reasonable steps to protect sensitive or restricted institutional data that you may have access to in the course of business and the normal execution of your job.
- You will access only the information you need to perform your university-assigned responsibilities.
- You will make every reasonable effort to maintain privacy of the data. This includes minimizing exposure of identifiable institutional data.
- You will share sensitive or restricted institutional data only with those who are explicitly authorized to access it under applicable laws, regulations, policies, standards, and procedures.
- You will not share your account information or password with others.
- You will sign out of institutional data systems and applications when not using them.
- You will store under secure conditions all data that you obtain from on-line pages, data warehouse or extracted datasets, including printed data as well as on-line transmissions of data (email, fax). Using and storing Social Security Numbers is strongly discouraged.
- You will encrypt confidential information on my university-owned computer, laptop, mobile device or removable storage device (e.g. thumb drive) whenever possible.
- You will be a responsible user of data, whether it is data relating to your own unit or another unit.
- You will make every reasonable effort to interpret data accurately and in a professional manner.
- You will make every reasonable attempt to maintain the integrity of the data. This includes making only the changes that you are authorized to make and doing so in an appropriate manner.
- You will report any actions which violate confidentiality to your supervisor or the Information Technology Security Officer.