Real-Time Crime Data Integration and Analysis Platform

In the fast-paced realm of law enforcement, timely access to integrated crime data is crucial for effective decision-making and resource allocation. Our SME is seeking a data engineering solution that consolidates crime data from various sources—such as CCTV, incident reports, and social media—and processes it in real-time for actionable insights. The proposed platform will utilize Apache Kafka for event streaming to capture real-time data, while Spark will facilitate distributed data processing. Databricks will be employed for advanced analytics and machine learning operations (MLOps), ensuring the platform adapts and learns from new data continuously. Airflow will manage complex data workflows, and dbt will enable reliable data transformation to improve data observability and accuracy. This platform is essential for law enforcement agencies to predict crime hotspots, optimize patrol routes, and enhance public safety strategies. By providing a comprehensive data mesh architecture, the solution will ensure scalability and flexibility to accommodate future data sources and analytics capabilities.