Real-Time Data Infrastructure for Personalized Learning Pathways

Our SME EdTech company is on a mission to transform K-12 education through personalized learning experiences. We aim to build a robust data infrastructure that processes and analyzes student engagement data in real-time, allowing us to tailor educational content to individual learning needs. The project involves designing a scalable data architecture with technologies like Apache Kafka for event streaming, Apache Spark for big data processing, and Snowflake or BigQuery for cloud data warehousing. Airflow will be used for orchestrating data workflows, while dbt will handle transformation processes to ensure data quality and consistency. Key deliverables include setting up data pipelines, implementing data observability methods, and integrating MLOps practices to automate and manage machine learning models that recommend personalized learning pathways. This system must support high volume and low latency to provide educators and learners with timely insights. The successful execution of this project will position our platform as a leader in adaptive learning solutions, driving engagement and improving educational outcomes.