Reference Architecture for Government Transport Agencies
This architecture supports data-driven transport operations to deliver enhanced passenger services, predictive maintenance and multimodal intelligence.

Transport data integration and intelligence
This architecture enables data-driven transport operations through proven integration patterns. It helps government agencies unify ticketing, traffic monitoring and GIS systems to deliver enhanced passenger services, predictive maintenance and multimodal intelligence.
- Unified passenger experience: Integrate ticketing, real-time information and journey planning across all transport modes for seamless passenger services
- Operational excellence: Enable predictive maintenance, dynamic scheduling and resource optimization through AI-powered insights from unified transport data
- Evidence-based decision-making: Support policy development and network planning with comprehensive analytics spanning passenger behavior, service performance and infrastructure utilization
- Regulatory compliance and reporting: Streamline compliance processes with automated data lineage, audit trails and standardized reporting across government requirements
Modernize transport operations with unified lakehouse architecture
1. Data sources and ingestion
- Real-time transport operations: Ticketing systems, traffic monitoring sensors and GTFS real-time feeds deliver live passenger flows, network performance and geospatial service data. Auto Loader incrementally processes files as they arrive in cloud storage, while Structured Streaming handles real-time data feeds.
- Geospatial infrastructure systems: GIS platforms and spatial-aware datasets provide the location-intelligent backbone essential for transport operations, where every data point — from assets to traffic flows to road disruption — carries precise geographic coordinates for network-wide analysis
- Corporate data systems: Government enterprise systems, including HR, finance, procurement and asset management, alongside compliance databases and unstructured policy documents (transport regulations, operational procedures, safety guidelines), provide organizational context, regulatory requirements and institutional knowledge for evidence-based transport decision-making
- Flexible ingestion patterns: Lakeflow Connect provides CDC ingestion from operational databases and Lakehouse Federation enables gradual migration from legacy systems, while API ingestion and message bus with Structured Streaming handle real-time feeds from transport sensors, GTFS systems and external data providers.
2. Data governance and management
- Unity Catalog: Centralizes metadata governance and automated data discovery across classified and unclassified transport datasets, with fine-grained access controls for sensitive passenger information, operational data and government assets. Built-in data lineage tracking ensures compliance with privacy regulations, security classifications and government transparency requirements while enabling secure data discovery and classification workflows.
- Multimodal data integration: Unifies real-time streams (ticketing, traffic sensors) and batch feeds (schedule updates, asset inventories) with geospatial datasets (GIS, road disruptions) into a common H3 hexagon indexing model. Delta Lake ACID transactions guarantee consistency and reliability across buses, trains, trams, ferries and cycling networks for seamless, location-aware analytics.
- System tables and auditability: Audit trails are captured and stored in dedicated system tables, recording with timestamps and user details. This ensures rigorous regulatory compliance, supports forensic analysis and upholds government transparency standards.
3. Analytics and decision support
- Real-time multimodal dashboards: Databricks SQL delivers live visualizations of on-time performance, passenger volumes and service reliability via AI/BI Dashboards, Tableau and Power BI
- Policy Q&A and natural language insights: Agentic AI chatbots answer regulatory and operational questions directly from transport data
- Passenger counting and capacity forecasting: AI-driven models predict ridership trends and optimize service planning using real-time and historical datasets
- Advanced geospatial visualization: Databricks Apps delivers interactive multilayer mapping interfaces where users can toggle between transport modes — buses, trains, trams, cycling lanes — overlaying H3-indexed performance data, real-time incidents, passenger flows and route analytics for comprehensive multimodal network visualization and operational decision-making
4. Secured data sharing
- Clean room collaboration: Share sensitive transport datasets with partner agencies in secure, governed environments using Delta Sharing, enforcing fine-grained access controls and audit logs
- Interagency private exchange: Seamlessly distribute curated multimodal data to federal, state and local authorities via open Delta Sharing protocols, enabling synchronized operational planning
- Public data portals: Publish anonymized GTFS feeds, road crash statistics and network performance metrics to citizens and developers, supporting transparency and civic innovation
- Conditional access and revocation: Define time-bound, role-based entitlements for external consumers, with real-time revocation capabilities to maintain data security and compliance
Benefits
- Accelerated decision-making with real-time analytics and AI-driven insights for rapid response to service disruptions and demand spikes
- Optimized operations and reduced costs through predictive maintenance, dynamic scheduling and resource utilization powered by unified transport data
- Enhanced transparency and compliance via centralized governance, automated audit trails and secure, fine-grained data sharing across government agencies