Building a High-Performance Analytics Platform at Trillion-Record Scale

A leading U.S.-based enterprise operating in the healthcare supply and services ecosystem partnered with Connective to build and enhance a mission-critical analytics and insights platform used by external consultants and enterprise customers. The platform aggregated massive volumes of transactional and procurement data and was designed to support advanced analytics at scale, but faced challenges related to performance, scalability, and usability as adoption increased. Connective embedded with the client’s product and delivery teams to accelerate delivery, improve system performance, and unlock actionable insights through data engineering, full-stack development, and early-stage AI enablement. Industry: Healthcare supply chain & analytics Operating Model: B2B platform supporting enterprise healthcare systems and facilities Scale: Trillions of data records across hundreds of thousands of systems The client had invested heavily in collecting and warehousing data and was focused on monetizing that data through advanced analytics, benchmarking, and insights delivered via a purpose-built software platform. While the platform was relatively greenfield in nature, rapid growth in data volume and usage introduced new technical and operational challenges.

The analytics platform had a strong vision but faced several challenges as it scaled:

• Extremely large datasets caused dashboards and reports to time out (often exceeding 2–3 minutes per request)

• Limited data pre-aggregation and inefficient query patterns constrained performance

• Consultants struggled to surface insights quickly during live customer engagements

• Growing demand for self-service analytics and data-driven recommendations

• Ongoing ingestion of new data feeds increased complexity and performance risk

Without intervention, these limitations threatened user experience, adoption, and the platform’s long-term value proposition.

Connective joined the engagement using an embedded, player–coach model, integrating directly into the client’s product, engineering, and data teams. The engagement spanned strategy through execution and included: Product & Delivery Enablement

• Embedded product and engineering leadership support

• Ongoing backlog refinement and prioritization

• Close collaboration with internal product owners and business stakeholders

Data Engineering & Performance Optimization

• Redesigned ETL pipelines to pre-aggregate high-volume datasets

• Optimized queries operating across trillions of records

• Reduced request times from minutes to seconds (e.g., ~105 seconds to under 2 seconds)

• Continued ingestion of new data feeds from additional clients and data sources while maintaining performance and reliability

Full-Stack Application Development

• Front-end dashboard and data visualization enhancements

• Backend API optimizations to support scalable, performant data access

• Continuous refinement of how complex data was presented for human decision-making

Architecture

• Cloud-native deployment on AWS

• React front end

• .NET Core API layer

• PostgreSQL and Databricks-based data platform

The resulting platform provided:

• Fast, reliable access to massive and continuously growing datasets

• Intuitive dashboards, tables, and visualizations designed for real-world consulting workflows

• Clear benchmarking across peer groups and cohorts

• Actionable insights surfaced in a digestible, consultant-friendly format

In addition, Connective contributed enhancements to the client’s internal design system, ensuring consistency, scalability, and reusability across the broader application ecosystem.

• Page and report load times reduced from minutes to seconds

• Improved consultant productivity and confidence during client engagements

• Increased platform adoption and retention

• Enabled more informed, data-driven recommendations for enterprise customers

While direct revenue attribution was difficult due to contract structures, usage, engagement, and adoption metrics demonstrated strong and growing platform value.

The engagement remains active, with Connective continuing to:

• Add new analytics features and capabilities

• Refine dashboards based on real user feedback

• Scale the platform as new data feeds, data types, and sources are onboarded

• Support data ingestion from multiple clients with varying governance models, data quality, and cleanliness standards while maintaining performance and trust.