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In this case study:
Overview
A large U.S. municipal transportation authority serving a major metropolitan region manages complex transportation and curbside operations for millions of residents and visitors. With more than 6,000 employees and responsibility for critical urban mobility infrastructure, the agency is recognized as a leader in public sector innovation and data-driven operations.
To support its mission, the authority set out to modernize the systems behind one of its most data-intensive functions: parking operations and revenue management.
The Challenge: High Volume, High Cost, Low Agility
The agency relied on a legacy Oracle-based environment to manage:
- Real-time parking meter activity
- Payment and transaction processing
- Operational and financial analytics
- Coin reconciliation and meter data pipelines
But the environment was becoming a barrier to progress:
- Heavy daily processing loads - Some core processes ran up to six hours per day across 110 GB of transaction data.
- Rising licensing and infrastructure costs tied to legacy architecture.
- Limited real-time visibility, making it difficult to respond dynamically to demand.
- Constrained analytics, reducing the agency’s ability to support advanced pricing and operational strategies.
The authority needed more than a lift-and-shift. It needed a scalable, modern data platform capable of supporting real-time operations, advanced analytics, and future AI use cases.
The Solution: Rebuilding the Data Core on Azure and Microsoft Fabric
The agency partnered with Quisitive to re-platform its Oracle environment to a modern Azure-based architecture centered on Microsoft Fabric.
The transformation includes:
- Re-platforming Oracle tables into a modern data foundation in Azure SQL leveraging deep SQL skill sets, reducing the number of tables, and improving performance on the legacy design
- Leveraging the rich feature set of Fabric mirroring to streamline data availability for analytics
- Deploying Azure SQL, Microsoft Fabric, Microsoft Purview, and Power BI for an integrated data, governance, and analytics stack
- Redesigning daily, monthly, and quarterly workflows to meet strict performance and reliability targets
- Embedding data governance and compliance from the start using Azure-native capabilities
Fabric enables the agency to move from batch-bound processing to real-time analytics, creating the foundation for AI-powered insights and operational decision support.
Delivery follows an agile model with continuous stakeholder alignment, ensuring modernization happens without disrupting mission-critical public services.
The Impact: Cost Optimization + Revenue Growth at Public-Sector Scale
This initiative is not just IT modernization. It directly reshapes the financial and operational model of a major public agency.
Cost Savings
By retiring legacy Oracle licensing and infrastructure, the agency expects to save more than $2M annually.
New Revenue Potential
With real-time data and analytics in place, the authority can support dynamic parking pricing strategies, projected to generate additional revenue.
Operational Efficiency
- Streamlined data pipelines
- Automated processing
- Reduced reliance on manual reconciliation
Together, these improvements reduce processing time, improve data accuracy, and allow teams to focus on higher-value work.
Future-Ready Architecture
The Azure and Fabric-based platform delivers:
- Elastic scalability
- Stronger governance and compliance
- A foundation for AI and advanced analytics
This positions the agency as a data-driven leader in public-sector transportation, capable of adapting to changing urban demand and policy needs.
Why This Matters
For public agencies, parking and mobility data are no longer back-office systems - they are strategic levers for:
- Revenue optimization
- Equity and policy-driven pricing
- Real-time operational management
- Public transparency and accountability
By modernizing its core data architecture, this transportation authority has moved from legacy constraints to a platform that supports real-time decision-making, financial optimization, and AI readiness.
