In the healthcare sector, data isn't just "info"—it’s the backbone of patient outcomes. For a premier US-based healthcare network, managing 738 Qlik Sense applications across 4,200 users had become an obstacle to agility. The goal was clear: move beyond fragmented legacy systems to a unified, AI-ready future.

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The Complexity of Clinical Data

‍The challenge wasn't just the sheer volume of data (over 2TB), but the diversity of it. From clinical metrics in EPIC Clarity to Health-Related Social Needs (HRSN) and Vizient benchmarks, the client needed a single source of truth that didn't sacrifice performance for scale.

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The Engineering Strategy

Partnering with Exponentia.ai, the healthcare network embarked on a structured migration to Microsoft Fabric:

• Thorough Evaluation: We didn't just move data; we performed a detailed gap analysis of the existing Qlik environment to ensure the new architecture was future-proof.

• Pipeline Modernization: We transitioned over 100 data pipelines, ensuring that the extract and transform processes were optimized for the Fabric SaaS environment.

• AI Readiness: By centralizing business logic, we paved the way for seamless AI integration, allowing for deeper insights into patient care and operational efficiency.

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Outcomes that Matter

‍The results speak for themselves. Beyond the 20% cost savings compared to their legacy environment, the client now operates on a structured, analytics-ready foundation. With a team of 20+ engineers now proficient in Fabric, the network is no longer just "managing" data - they are leading with it.

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Conclusion: From Infrastructure Hurdles to AI Readiness

By accelerating the shift from Qlik to Fabric, the healthcare network successfully reduced migration complexity and established a structured, analytics-ready data foundation. This transformation has moved the institution beyond managing infrastructure complexity toward driving trusted, data-led insights. With a scalable SaaS platform now in place, the organization is positioned to enable seamless AI integration, ensuring that every data point contributes to better decision-making and enhanced patient care

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