To facilitate the discovery of high-value insights through data that:
Support efforts by Princeton administrators to advance mission-critical decision making
Contribute to academic research and dialogue on higher education
Background
As an internal consulting service to the University, we partner with institutional leaders, staff and researchers to carry out data analytics projects. Some projects may include exploring, at the request of our administrative unit partners, the optimal uses and potential of existing Princeton data. For other projects we employ advanced data analytics techniques to focus on collaborators’ specific questions of high operational and research value.
In July 2017 Princeton University’s former Provost David S. Lee, Chemical Bank Chairman's Professor of Economics and Public Affairs and associated faculty member of the Industrial Relations Section, established the Initiative for Data Exploration and Analytics (IDEAS) for Higher Education within the Woodrow Wilson School of Public and International Affairs.
Graduate Admissions
Expand access to graduate educational opportunities
Diversity & Inclusion
Advance opportunity in higher education
Academic Job Market
Catalogue faculty in U.S. institutions and identify trends
Analytics in Higher Ed
Help institutions improve operations and manage risk
Alumni Outcomes
Evaluate the value and impact of higher education
Education Policies
Examine institutions in public and political contexts
Discovering High-Value and High-Impact Opportunities
We identify opportunities to leverage data analytics
Engage in ongoing conversations with researchers, administrators, and other key stakeholders at Princeton and beyond
Conduct reviews of literature and best practices
Choosing the Right Data and Combining it in Unique Ways
We work creatively in pursuit of our research questions
Identify viable internal and external data sets that best answer our research questions
Facilitate secure access to those data for quick, targeted analyses
Apply customized algorithms and validation processes to combine datasets creatively, revealing unique insights
Employing Machine Learning and Predictive Models
We explore the use of many analytics tools and resources
Employ machine learning to extract useful information out of data
Build predictive models based on patterns in the data revealed through machine learning
Leverage the expertise of software developers, Princeton researchers, and other partners
Integrating Analytics into Existing Decision Processes
We provide tools to empower decisions makers
We carry out projects that enable collaborators to formulate precise questions
We provide guidance to assist our partners to identify the right solutions