Real-Time Learning Engagement Analytics Platform Development

Our online learning platform is experiencing a surge in user activity, which has highlighted the need for an advanced analytics solution to monitor and boost learner engagement in real-time. We aim to build a comprehensive data pipeline that captures live user interactions, processes them efficiently, and delivers actionable insights via an intuitive dashboard. The project will utilize Apache Kafka for event streaming, Spark for data processing, and Snowflake or BigQuery for storage and querying. Airflow will orchestrate workflows, while dbt will handle data transformations. Databricks will provide a robust environment for machine learning operations, allowing for real-time adaptability of learning content based on engagement analytics. The solution is expected to provide course creators with a deeper understanding of learner behaviors, identify at-risk students, and optimize course content for improved outcomes. This project is critical for maintaining competitive advantage in the rapidly evolving online education sector. By implementing this analytics platform, we anticipate significant improvements in learner retention and satisfaction.