Empowering students with real-world data: How the Raymond A. Mason School of Business is shaping the future of data education
In an era where data is at the heart of business strategy and decision-making, William & Mary's Raymond A. Mason School of Business students are gaining the skills and experience necessary to thrive in the data-driven world. Thanks to the innovative use of the Virginia Open Data Portal (ODP), professors are equipping the next generation of business leaders with the technical tools to analyze data and the communication skills to make sense of it for broader audiences.
The Virginia Open Data Portal, which boasts more than 13,000 datasets from federal, state, and local sources, provides a wealth of information for students. This platform is more than just a resource; it's a gateway to meaningful analysis, empowering Virginians to interpret data across various topics, from public health to economics.
At the Raymond A. Mason School of Business, Professor Guillermo Rodriguez-Abitia and Professor Monica Tremblay are leading the charge to integrate the portal into their classroom projects, challenging students to extract insights and deliver data-driven solutions to real-world issues.
From Data Cleaning to Decision-Making
In Professor Rodriguez-Abitia's database class, students dive into the complexities of data by selecting topics of their own choosing and sourcing relevant datasets from the Virginia ODP. They are tasked with consolidating data from multiple sources, cleaning it, and transforming it into a unified format for analysis.
"The first step in data analysis is understanding the data itself," says Professor Rodriguez-Abitia. "You can't make informed decisions without clean data. I want my students to learn how to work with data and navigate the challenges that come with it—missing values, inconsistencies, and formatting issues."
Once the data is prepared, students move on to more advanced technical tasks. They build data warehouses, using tools like Alteryx and MySQL to create tables and feed them with the necessary data automatically. The final stage of the project requires students to apply their insights to real-world decision-making by designing dashboards in Tableau to visualize their findings. These dashboards are the cornerstone of the student's analysis, enabling them to communicate their results effectively.
"The ability to turn data into actionable insights is a critical skill," Rodriguez-Abitia continues. "Building these dashboards helps students see the bigger picture and communicate their conclusions in a way that is accessible to non-technical audiences."
Predicting the Future with Machine Learning
In Professor Tremblay's Machine Learning 1 course, students take a deep dive into predictive analytics, applying machine learning techniques to real-world datasets sourced from the Virginia ODP. The focus here is on developing predictive models that can solve practical problems, whether forecasting trends or identifying patterns in complex data.
Students are introduced to core machine learning concepts such as linear regression, logistic regression, and k-nearest neighbors. Using DataCamp Workspaces, they clean data, perform exploratory data analysis (EDA), and engineer features to improve the accuracy of their models. Along the way, they learn how to evaluate their models using metrics such as accuracy, precision, and mean squared error.
But the technical work doesn't stop there. Students must present their models and findings to executive partners, showing how data science intersects with business decision-making.
"Machine learning is not just about crunching numbers," says Professor Tremblay. "It's about applying these techniques to drive decisions that can have a meaningful impact. By presenting their findings to industry partners, students get invaluable feedback that enhances their technical skills and strengthens their ability to communicate complex concepts to non-technical audiences."
The course culminates in a poster presentation, where students showcase their projects and summarize their key findings. This final exercise helps students refine their ability to communicate technical information in a way that's clear and accessible to stakeholders.
Real-World Impact: Students Address Critical Issues
For many students, these classes represent more than just academic exercises—they are opportunities to apply their skills to issues that matter. One student project focused on food insecurity in Virginia, using machine learning to predict trends and identify the most vulnerable regions.
"Our project aimed to leverage machine learning to analyze and predict food insecurity trends in Virginia," says one of the students. "While our model is not designed for long-term forecasting, it offers valuable insights for regions with limited data, enabling better resource allocation. Addressing food insecurity requires a strategic approach, and we hope our work sparks meaningful discussions on how data can be used to guide impactful interventions both locally and globally."
These real-world applications are a key part of the learning process for both professors. "By engaging with datasets on real-world issues, students are not only honing their technical skills but also gaining a deeper understanding of the broader societal implications of data science," says Rodriguez-Abitia. "This is the future of business education: empowering students to solve real-world problems with data."
Preparing Students for the Future
Integrating the Virginia ODP into William & Mary's business curriculum is a significant step toward preparing students for the data-driven future of business. As more and more industries turn to data science to inform their decisions, the ability to work with large datasets and communicate findings effectively will become an essential skill.
"Whether students go on to work in business, healthcare, government, or technology, the ability to analyze data and communicate insights will be invaluable," concludes Professor Tremblay. "Our goal is to prepare them to make data-driven decisions that will positively impact whatever field they choose."
Attribution of this story goes to the communications team at the Office of Data Governance and Analytics (ODGA) and was published in early 2025 under the title "Innovative Uses in Education: William & Mary." The story has been edited and enhanced to suit the audience of the Mason School community.
