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The client's existing data infrastructure relied on Azure SQL with in-memory computations and monolithic stored procedures, causing severe performance bottlenecks. Processing 270,000+ records took over 15 minutes, with escalating delays due to hourly data updates. The system lacked scalability, required full rebuilds for minor changes, and could not support dynamic updates or cloud-native efficiencies.
A real estate platform managing large volumes of property, pricing, tax, and geographic data across the U.S., requiring scalable analytics capabilities.
The modernized architecture enables real-time analytics on exponentially growing datasets, reducing full rebuild times from hours to minutes. Dynamic update capabilities eliminate system-wide disruptions for minor data changes, while cloud-native scalability ensures long-term adaptability. Performance improvements directly translate to faster business decisions and 80%+ reduction in infrastructure costs compared to legacy systems.