Real-time Analytics Platform for Enhancing Special Education Outcomes

As an enterprise in the Special Education sector, we're dedicated to transforming how data informs educational strategies and outcomes. Our project seeks to build a real-time analytics platform that utilizes event streaming and data mesh architecture. By employing tools like Apache Kafka and Spark, we aim to process data from various sources, such as student performance metrics, behavioral observations, and environmental factors, in real-time. This platform will integrate with existing educational and analytics systems (using technologies like Airflow, dbt, Snowflake, or BigQuery) to ensure seamless data flow and insights generation. Key objectives include enhancing data observability, ensuring robust data governance, and facilitating a feedback loop where educators can make informed decisions promptly. With the inclusion of MLOps, the platform will support adaptive learning models that cater to individual student needs, fostering a more inclusive educational environment. This initiative not only seeks to improve the efficacy of special education programs but also to demonstrate compliance with evolving educational standards and regulations.