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Driving Efficiencies and Insights with Data Insights Analytics for Automotive Services

How NRI Helped a Leading Automotive Dealer Cut Analytics Costs by 50% and Boost Performance 10×

Business situation

One of the largest privately owned automotive dealer groups in the United States—operating over 40 franchise locations and representing more than 20 vehicle brands—was struggling with an aging analytics platform on Microsoft Azure. Reporting processes had become slow, siloed, and expensive, threatening the dealer group’s ability to scale and deliver timely insights that drive sales and service excellence.

Considerations

Reduce the total cost of analytics infrastructure without sacrificing performance.
Eliminate data silos across multiple dealerships to enable a single source of truth.
Implement a high-throughput solution capable of handling growing data volumes and complex queries.

Gearing Up the Transformation

Before diving into our technical overhaul, NRI’s Data Insights team collaborated closely with the dealer group to translate the key considerations—cost efficiency, unified access, and scalable performance—into a clear, actionable roadmap. By mapping out every data source from parts inventories to customer feedback, we ensured each requirement had a targeted strategy. This preparatory phase set the stage for a seamless migration and performance optimization, keeping both budget and business continuity top of mind.

With stakeholders aligned on success metrics and priorities, we established a phased delivery plan that minimized disruption across 40+ dealerships. Executive sponsors and department leads participated in steering sessions to validate milestones, while hands-on workshops shaped use cases like real-time showroom analytics and inventory turnover dashboards. This cohesive groundwork ensured the subsequent solution deployment would be both rapid and resilient.

Our solution

NRI began by consolidating the dealer group’s fragmented on-premises and regional databases into a single Azure Data Lake. This centralized repository eliminated data silos, creating a unified source of truth that streamlined data ingestion and laid the groundwork for all downstream analytics workflows. By carefully mapping each data feed and validating quality at every stage, we ensured the migration was seamless and that business continuity remained uninterrupted.
Building on this foundation, we implemented Microsoft Fabric to supplant the legacy, memory-based database environment. Fabric’s integrated suite—combining data engineering, warehousing, and real-time analytics—provided low-latency, self-service reporting across all 40+ dealerships. Stakeholders from general managers to service technicians could now tap into the same set of reliable insights, empowering faster, more informed decisions without waiting for IT backlogs to clear. To demonstrate measurable cost and performance benefits, NRI then developed a proof-of-concept pipeline using Azure Databricks alongside Fabric. By fine-tuning Spark job configurations and streamlining ETL processes, we slashed query latency and reduced infrastructure overhead. This optimized pipeline not only validated a 50% reduction in analytics costs but also set the stage for continuous improvements and future AI-driven enhancements.

Capabilities Applied

Advisory & Planning
Intelligent Data & AI
Empowered Business Platforms

Technologies Utilized

Microsoft Azure Data Lake & Synapse Analytics
Power BI
Microsoft Fabric
Azure Databricks

Results

The analytics modernization delivered transformative business value by slashing costs, turbocharging performance, and unifying data operations—all while laying the groundwork for advanced, AI-fueled insights that will drive future innovation.
50% reduction in analytics infrastructure spending, freeing budget for strategic initiatives
10× faster query performance, enabling real-time exploration of large datasets
Unified data platform spanning 40+ dealerships, ensuring consistent, reliable insights
Interactive dashboards that equip leadership and frontline teams with on-demand KPIs
Scalable architecture primed for AI-driven use cases like predictive maintenance and personalized customer experiences

Ready to take things further?