Real-Time Data Infrastructure for Optimized Renewable Energy Management

As a leader in the renewable energy sector, our enterprise is committed to optimizing the performance and sustainability of our energy assets. The current challenge lies in the lack of a unified, real-time data platform to manage and derive actionable insights from our diverse energy sources, including solar, wind, and hydroelectric. The proposed project involves designing and implementing a scalable data infrastructure leveraging Apache Kafka for event streaming and Spark for real-time analytics. By integrating data mesh principles, the system will ensure data accessibility across different teams, while MLOps will support continuous model deployment for predictive maintenance. The use of technologies like Airflow and dbt will streamline data workflows, ensuring data quality and observability. Platforms such as Snowflake or BigQuery will offer the necessary scalability and storage capabilities. The success of this project will empower our teams to make data-driven decisions, enhance operational efficiency, and reduce downtime, ultimately leading to a more sustainable and cost-effective energy supply.