By Insight Editor / 7 Dec 2021 / Topics: Microsoft Azure Analytics Data and AI
Facts at a glance
Client industry:
Public sector
Size of company:
1,400 employees
Challenge:
A major metropolitan fire department needed to migrate from their existing Oracle® database into a modern cloud platform to better support their real-time and long-term reporting needs.
Solution:
Insight deployed a modern data architecture, leveraging Azure® Data Factory, Databricks®, Delta Lake, Azure SQL and SQL Server® Analytics Services (SSAS). This served as the foundation for the development of a real-time reporting dashboard to provide up-to-date insights on emergency events as well as the status and locations of equipment and response personnel.
Results
- Improved staging of 15,000 vehicles and assets
- Reduced emergency response times
- Enabled the IT team to manage data systems in house
- Foundation for future predictive analytics capabilities
Solution area:
Digital Innovation
In 2019, one major metropolitan fire department recognized an opportunity to improve its services to the community by modernizing its existing data environment. By making the shift from a brittle, legacy data system to a cloud-based infrastructure, leaders hoped to better position the 135-year-old organization to address current and future challenges with real-time intelligence.
For many years, the fire department had relied on an Oracle database to manage all incoming data and outbound reporting. This included information collected from emergency calls, first responders and GPS-tracked equipment. But a high volume of records, numbering in the hundreds of millions, created bandwidth and performance challenges.
Additionally, while they had the ability to generate basic reports, IT leaders realized that leveraging their real-time system for broader analytics didn’t align to best practices. The organization determined it was time to make the switch to a modern, cloud-based data platform which would enable a unified view of all assets and events while supporting both real-time and long-term reporting needs.
When one of Microsoft’s cloud and data specialists heard about these challenges, he recommended Insight for the project. Since the fire department had previously turned to Insight for support on cloud and data center initiatives, the CIO and his team felt confident we could help them reach their goals.
With this partnership in place, an Insight architect and senior systems engineer began implementing a Proof of Concept (POC) to establish critical features and feasibility for the project.
They worked closely with the client’s IT team to pull data from the legacy Oracle database and other peripheral systems into a centralized data lake. Azure Data Factory was leveraged for ingestion, with Databricks used to support processing before landing the data in Delta Lake. The data was then written to Azure SQL and a semantic model was developed through SQL Server Analytics Services, allowing sample reports to be served up through Power BI®.
The POC was successfully completed within four weeks, and IT leaders immediately recognized the value of the unified reporting platform and the ability to bring in real-time data to support data science projects.
With the POC approved, Insight’s team began implementing the full data modernization project at scale. They leveraged Insight’s repeatable Extract, Transform, Load (ETL) framework to automate significant portions of the infrastructure deployment, data cleansing and configuration processes. This dramatically accelerated project timelines and ultimately meant the new data architecture was up and running in a matter of weeks — rather than months.
While the modern data architecture greatly improved the way the fire department managed its data, leaders had additional goals to leverage their data in support of daily operations. They wanted to add a real-time channel to the reporting infrastructure to serve up critical information through a centralized dashboard, including:
The primary data sources for the dashboard included the city’s 911 system, as well as GPS trackers from fire department equipment and personnel. This data is reported at regular intervals to track activity and movement over time. The goal was to display this information on a map which would automatically update with locations and incidents. This view would need to be as accurate and up-to-date as possible to facilitate rapid decision-making on resource and equipment deployments.
Once again, Insight’s data and AI team worked closely with the organization’s internal IT department to develop a POC for this phase of the project. The newly centralized data architecture — combined with the Insight’s automated ETL framework — provided a robust foundation for accelerated development and deployment.
Insight’s team leveraged Azure Event Hubs to ingest event data at rates of up to 100+/second. A Databricks analytics platform with Spark structured streaming was then used to stream events from the ingestion platform into Delta Lake. This served as the high-performance, big data ACID store to capture and store processed data, allowing it to be merged with previous records. Finally, Power BI was used for real-time visualization with automatic updates triggered directly by data changes in Delta Lake.
In just a few weeks, the POC was complete and approved for full production. The full-scale solution was quickly delivered, providing a single-pane-of-glass view of city-wide emergency response data.
With the modern data architecture and real-time reporting dashboard in place, the fire department now has greater visibility into current events and long-term trends.
Fire chiefs regularly rely on real-time information to optimize “move up” operations. As events appear on the map, nearby resources are quickly rerouted to respond to incidents in progress or prepare for potential future incidents. This has enabled improved staging of 15,000 vehicles and assets and helped to reduce emergency response times.
Furthermore, this system lays the groundwork for future predictive capabilities. With the incorporation of machine learning, the organization may soon be able to analyze historical trends and automatically identify preemptive placement of resources.
Throughout this engagement, Insight provided the education and training to enable the internal IT team to perform their own self-service. This collaborative approach was critical in allowing the organization to maintain ownership over their data architecture, manage their own reporting and evolve their systems as needed over time.
By building on their work with Insight, the fire department is equipped not only to better serve its community today, but also to transform the way it responds to challenges in the future.
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