Real-time Student Success Data Platform Using Data Mesh Architecture

As a leading university, we understand the critical role of data in shaping the academic success of our students. To achieve a holistic view of student performance and support tailored interventions, we are embarking on building a comprehensive data platform based on a data mesh architecture. This will involve integrating disparate data sources—such as learning management systems, student information systems, and engagement platforms—into a unified, real-time analytics solution. Key technologies include Apache Kafka for event streaming, Spark for data processing, and Snowflake for data warehousing. Our vision is to empower academic departments with timely insights that inform curriculum adjustments and personalized student support. This project also requires setting up MLOps pipelines for deploying predictive models that alert faculty to at-risk students. By utilizing Airflow and dbt, we'll ensure data observability and pipeline orchestration. The successful implementation of this platform is expected to significantly enhance academic outcomes and student retention rates.