IR&DS, Student Data Stewardship, and Data Governance have partnered to offer some thoughts about how to present, interpret, and distribute student information responsibly. The project was designed to introduce some of the common pitfalls that those who regularly prepare and analyze data may experience. We have compiled a list of risks and best practices for working with student data that is not intended to be exhaustive, but can be used as a starting point for conversation or simply food for thought. To help illustrate these concepts, we also created three fictional scenarios that depict some of the ways that data might be misused or misinterpreted. You can explore the list and scenarios at Risks and Best Practices for Working With Student Data page on the SIRIS website.
Have you wished for a place to find out information about the university's data elements? We may be able to help you with your quest. Stanford's Data Governance program strives to improve the effectiveness and usefulness of the university's data elements by documenting what the data represents, where the data is stored and how the data should be used in Stanford’s Data Governance Center (DGC). The DGC includes a business glossary to let you know what the data represents; reporting index, code sets and decode values, along with documentation of data sources to so you know where the data is stored; business rules, best practices, and appropriate usage so you know how the data should be used. In addition to the DGC, we also have infographics documenting relations between complex areas and best practices on data usage (data stewardship maps).
IR&DS has published a new webpage that presents the findings of a recent major study of PhD alumni employment outcomes. The study, undertaken by IR&DS in collaboration with the Office for the Vice Provost for Graduate Education (VPGE), examined the career paths of 2,420 doctoral alumni across two cohorts. The results of this study are available online here. The webpage is interactive and allows users to explore the data and findings from the study.
We are pleased to announce that Brijesh Rao is joining IR&DS as our new Director of Decision Support and Business Intelligence. Brijesh will lead the SIRIS project, the DSS warehouse, and will work to develop our strategy for delivering information for campus stakeholders. Brijesh has 20 years of experience providing business Intelligence solutions and analytics. He holds a Master’s in Computer Science and has lead multiple BI initiatives at various tech companies in the bay area, trying to address their reporting and analytical needs. He is passionate about data and the means to bring it to life visually. In addition, he loves to work with new technologies to answer old world problems and predict future trends.
Please welcome Shannon Monahan, who will be joining IR&DS as an Institutional Research Analyst. Shannon worked previously for the Office of Postdoctoral Affairs and brings with her a deep knowledge of the institution, technical proficiency, and years of experience in analyzing and reporting on a unique population at Stanford in support of policy review and decision-making. In 2018, Shannon was given the Inspiring Change Leadership Award by the School of Medicine in recognition of her professional abilities and commitment to the campus community. Shannon will be applying her expertise to a variety of new projects, including the development of improved reporting on graduate student financial support, and supporting the team's ongoing efforts on a range of topics.
Join us in welcoming Tallie Wetzel to IR&DS. She will be serving in the role of Assessment & Program Evaluation Analyst on the Assessment team. Her initial responsibilities will include supporting the administration, analysis and reporting on several institution-wide surveys. Prior to joining the Assessment team, Tallie worked for SRI International in the Education Division as a quantitative research analyst. Tallie brings to her position at Stanford many years of training and experience in wrangling large, complex, messy data for the purpose of better understanding problems and improving policy- and decision-making.