Real-Time Data Infrastructure for Enhanced Municipal Services

The objective of this project is to design and implement a robust real-time data infrastructure for our municipal services department. As a growing city, we manage an extensive array of services including water, electricity, waste management, and public safety. These services generate vast amounts of data that can be harnessed to improve decision-making and service delivery. The project will involve setting up a data mesh architecture that facilitates seamless integration and processing of data streams from various city departments. Utilizing technologies such as Apache Kafka for event streaming and Spark for processing, we aim to develop a real-time analytics platform. Additionally, Airflow will be employed for orchestrating complex data workflows, while dbt will assist in transforming and modeling data within Snowflake and BigQuery environments. By enabling MLOps capabilities, we will also incorporate machine learning models to predict service disruptions and optimize resource allocation. This initiative will lead to more informed decision-making and enhanced service reliability, ultimately improving the quality of life for our citizens.