Real-Time Urban Infrastructure Data Integration Platform

Urban planners face the challenge of making timely decisions based on complex and often fragmented data. This project will tackle these challenges by developing an advanced data integration platform that consolidates real-time data from various sources, such as traffic sensors, public transport systems, and environmental monitoring stations. Leveraging technologies like Apache Kafka for event streaming and Spark for data processing, the platform will ensure high throughput and low latency. Additionally, using Airflow for orchestration and dbt for transformation will provide seamless data pipelines. The platform will support Snowflake and BigQuery for storage and analytics, enabling urban planners to conduct real-time analysis and forecasting. By employing data mesh principles, the platform will ensure domain-oriented decentralization, allowing different city departments to leverage data independently while maintaining centralized governance. This project is crucial for cities aiming to enhance operational efficiency and sustainability through data-driven insights.