Challenge
A large public-sector aviation authority operating two major airports relied on an on-premises SQL environment that could only be queried during limited time windows. Heavy reporting workloads risked disrupting live operational systems that support airport activities.
Rather than replacing the existing platform, the organization needed a cloud-based data architecture that would preserve operational stability while expanding access to analytics. The challenge was to enable broader reporting and historical analysis without increasing load on mission-critical systems or introducing operational risk.
Solution
SDI designed and implemented a cloud-based analytics architecture using Microsoft Azure. A centralized data lake was created to mirror only the specific SQL tables required for reporting. Data was extracted during approved windows and orchestrated through Azure Data Factory’s ETL capabilities into cloud storage, where it could be structured for analytics and long-term historical use.
Curated datasets were delivered through Azure Synapse Analytics, enabling fast, scalable querying without directly accessing the operational system. By shifting complex data modeling and joins to the cloud layer, the solution reduced dependency on the source environment while delivering clean, analytics-ready datasets to Power BI for enterprise reporting.
Services Delivered
- Cloud data architecture design using Microsoft Azure
- Data lake implementation for analytics and historical archiving
- Controlled ETL processes aligned to operational query windows
- Azure Data Factory pipeline development
- Azure Synapse Analytics modeling and query optimization
- Reporting dataset design for Power BI
- Performance optimization to reduce load on source systems
- Analytics foundation for future use cases
Benefit
The organization gained centralized, cloud-based analytics without disrupting live airport operations. Reporting workloads were removed from the operational environment, improving system stability while enabling faster processing and more reliable dashboards.
Business users can now analyze data across multiple tables through Power BI without complex source-system joins, improving insight and usability. The new architecture also established a scalable foundation for future analytics initiatives, allowing the organization to expand data capabilities while preserving the integrity of its mission-critical systems.
