The Bren Student Data Exporer is an interactive dashboard that showcases career outcomes and admissions data for current students and recent alumni. It was developed with the intention of supporting:
- Prospective students in their decision-making as they explore the different degree programs at the Bren School
- Bren departments and staff with their reporting requirements
- All Bren communities and stakeholders from the past, present, and future by upholding data transparency and data integrity principles through an accessible application
Data are updated annually by Bren staff. Visit the wiki to review important information and detailed instructions for updating and maintaining the Bren Student Data Explorer.
.
├── bren-student-data-explorer/ # app directory
│ ├── r/ # fxns for building inputs & outputs
│ ├── text/ # static text elements
│ ├── www/ # app images, styles, google analytics
│ ├── global.R
│ ├── server.R
│ └── ui.R
│
├── data-cleaning/ # data cleaning scripts for processing application data
│
├── .gitignore
├── README.md
└── shiny-dashboard.Rproj
- February 2023, updates by Sam Shanny-Csik: refactored code base, added career data for MEDS and MESM graduating classes of 2022
- July 2024, updates by Sam Shanny-Csik, Jamie Montgomery, & Kat Le: added career data for MEDS and MESM graduating classes of 2023, added admissions data for the 2023 entering classes, refactored code for maps (
{tmap}
>{leaflet}
+ removed data wrangling from server to improve loading speeds) - October 2024, updates by Sam Shanny-Csik: redesigned career plots so that they are a bit easier to interpret, added a secondary table of job titles, and continued refactoring code (i.e. simplifying and removing unncessary code)
- November 2024, updates by Sam Shanny-Csik: updated demographics tab with 2024 incoming student data
- May 2025, updates by Sam Shanny-Csik: added career outcomes data for the graduating classes of 2024 and admissions data for the incoming classes of 2025; completed a major refactor to reorganize the file structure, establish a consistent data processing and cleaning pipeline, remove redundant code, and generalize functionality by replacing hard-coded values and text with dynamic, data- or user-defined inputs throughout.