Healthcare organizations are increasingly turning to unified data platforms to improve patient outcomes, streamline operations, and support advanced analytics. In 2025, Microsoft introduced Microsoft Fabric for Healthcare and Life Sciences, a tailored version of its Fabric platform that brings together data engineering, governance, analytics, and AI in a single environment. Early adopters are using this solution to break down long-standing data silos between clinical, operational, and research systems, enabling real-time insights that improve decision-making across the care journey.
The need for better data integration in healthcare is pressing. According to industry research, healthcare organizations generate vast amounts of structured and unstructured data every day, yet much of this information remains trapped in fragmented systems and legacy databases. By unifying data into a single, governed fabric with built-in compliance controls, Microsoft Fabric for Healthcare enables providers to improve analytics on patient outcomes, support AI-assisted diagnostics, and speed up clinical research, all while maintaining regulatory standards such as HIPAA.
Continue reading this blog to explore how Microsoft Fabric for Healthcare works in practice, what capabilities it brings to clinical and operational analytics , and how it helps healthcare organizations move from data fragmentation to actionable, AI-driven insights.
Key Takeaways Healthcare data is highly fragmented across clinical, operational, claims, imaging, and research systems, slowing down analytics and decision-making. Microsoft Fabric unifies data engineering, analytics, BI, and AI on OneLake, reducing silos and speeding up insights across healthcare teams. Built-in support for FHIR, OMOP, DICOM, CMS claims, and SDOH cuts data preparation time for clinical analytics and research. The medallion architecture enables reliable movement from raw healthcare data to analytics-ready insights with strong governance. Fabric supports real-time, population health, operational, and research use cases while maintaining compliance with healthcare regulations. Kanerika helps healthcare and life sciences organizations adopt Fabric faster using automation-led migration, governance setup, and scalable analytics solutions.
Why Healthcare Data Is So Hard to Work With Healthcare data is fragmented by design. Most organizations run dozens of systems in parallel, each created for a specific function rather than end-to-end analysis. As a result, clinical, operational, and financial data often sit in separate environments, making it difficult to connect the full picture of care delivery or performance.
Key Challenges Data spread across EHRs, PACS, claims systems, labs, and wearable devices A mix of structured data , semi-structured messages, and unstructured clinical text Strict regulations such as HIPAA, GDPR, and HITRUST that limit how data can be moved or shared No single, unified view of patient, operational, or financial data
Because of these limits, healthcare teams frequently work with incomplete or outdated information. This leads to slower decisions, duplicated records across departments, and insights that are discovered too late to drive meaningful action.
How Does Microsoft Fabric Simplify Healthcare Data Analytics? Microsoft Fabric takes a platform-first approach to healthcare analytics. Rather than stitching together multiple tools, it brings core analytics capabilities into one environment, making it easier for teams to work from the same data foundation. OneLake brings clinical, operational, financial, and research data together, making it easier to analyze information end-to-end.
What Makes This Simpler in Practice A single platform for data engineering, data warehousing, real-time analytics, data science, and Power BI OneLake as a shared storage layer, removing the need to copy data across services Prebuilt healthcare pipelines aligned with FHIR, OMOP, and DICOM standards A SaaS delivery model with automatic scaling and no infrastructure management
By reducing custom engineering and operational overhead, Fabric allows healthcare teams to move from raw data to usable insights much faster. In many cases, analytics initiatives that previously took months to stand up can now be rolled out step by step, with consistent governance and reuse across teams.
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Healthcare Data Solutions Inside Fabric Microsoft groups its healthcare-specific capabilities under the label “Healthcare data solutions.” Each one addresses a different part of the data challenge, and they are designed to work together within the same OneLake environment.
1. Healthcare Data Foundations This is the starting point for any deployment. It sets up your data estate using the FHIR R4 standard and a medallion architecture within OneLake, which organizes data across three increasingly refined layers.
The Bronze layer stores raw data in its original format. FHIR bundles, HL7 messages, DICOM metadata, claims CSVs, genomics files, and any other source data land here as the unchanging record of truth. Nothing is transformed or filtered at this stage, which means you always have the original data to fall back on. The Silver layer is where pre-built pipelines transform raw FHIR JSON into tabular structures stored in delta-parquet format. Patient IDs and references get harmonized across source systems at this stage, which makes cross-facility queries possible using standard SQL. This is also where the platform’s FHIR R4 data model comes into play, providing a flattened, queryable representation of clinical data without requiring custom engineering. The Gold layer contains business-ready, analytics-optimized data. This is what feeds Power BI dashboards, machine learning models, research cohorts, and executive reporting. Teams have cleaned, aggregated, and shaped this data for specific analytical use cases.
Built-in pipelines map your FHIR data from the Silver layer into the OMOP v5.4 Common Data Model in the Gold layer. OMOP is the standard used across clinical research for comparing drug exposures, tracking disease progression across populations, and running observational studies that span multiple institutions. If your organization takes part in multi-site research networks or needs to run analyses that follow OHDSI (Observational Health Data Sciences and Informatics) standards, this capability eliminates weeks or months of data preparation work.
This capability brings medical imaging metadata from X-rays, CT scans, and MRIs into OneLake alongside your clinical records. Researchers and clinicians can link imaging findings with lab results, diagnoses, and treatment histories without building custom integration pipelines. At HIMSS 2024, Microsoft announced a private preview of this feature, and it has since expanded to support broader use cases around AI-powered imaging analysis and multi-modal research.
4. Azure Health Data Services Integration A direct export path from Azure Health Data Services into OneLake. If your organization already manages FHIR data through Azure’s FHIR service, you can start running analytics in Fabric without rebuilding your ingestion pipeline. This is especially useful for organizations that have invested in Azure Health Data Services and want to extend their data into a broader analytics environment without duplicating infrastructure.
Streamlines the ingestion of Centers for Medicare & Medicaid Services (CMS) Claim and Claim Line Feed (CCLF) data into OneLake. Once inside the platform, claims data can be harmonized with clinical, imaging, and SDOH data to produce unified views of patient populations, payer performance, and reimbursement trends.
Ingests, harmonizes, and makes available public Social Determinants of Health datasets from national and international sources. Healthcare organizations can use this data to identify health-related social needs, assess community-level risk factors, and design more fair care programs. When combined with clinical and claims data in the same OneLake environment, SDOH data adds a critical dimension to population health analysis.
Enables organizations to send conversational data from Nuance’s Dragon Ambient eXperience (DAX) Copilot into Fabric. This includes audio files, transcripts, and draft clinical notes from patient-provider conversations. Once inside OneLake, this data can be analyzed alongside other clinical and operational data to generate insights around documentation quality, clinical workflows, and patient-provider communication patterns.
8. Multimodal AI Insights (Preview) Connects to healthcare AI models and APIs to extract structured information from unstructured data. For example, running discharge summaries or radiology reports through Azure AI Language’s Text Analytics for Health to pull out medical entities, clinical relationships, and diagnostic findings, then storing the results in OneLake for downstream analytics and model training .
Source: Microsoft Use Cases Across Healthcare 1. Clinical Decision Support With clinical data, lab results, imaging metadata, and conversational data all in the same platform, care teams can build real-time dashboards that surface a complete picture of patient status. Organizations are using this for early sepsis detection, ICU monitoring, flagging abnormal lab results before they get buried in the noise, and correlating imaging findings with clinical history for more accurate diagnosis.
2. Population Health Management Combining clinical records, social determinants data, claims history, and demographic information enables population-level analysis at a scale that was previously impractical. Teams can track trends in chronic disease, identify patients overdue for preventive screenings, rank risk across patient populations, and design targeted interventions. OMOP transformations make comparative studies across facilities and research networks significantly more practical.
3. Operational Efficiency Bed occupancy, patient flow, staffing patterns, surgical scheduling, supply chain usage, and ED wait times all produce data that can be centralized in Fabric. Some organizations use Fabric’s Real-Time Intelligence capability to process streaming data from medical devices, providing up-to-the-minute visibility into operational metrics that traditionally lagged by hours or days.
4. Revenue Cycle Optimization By bringing claims, clinical documentation, and payer data into the same environment, revenue cycle teams can identify denial patterns, catch coding errors before submission, track reimbursement timelines with full clinical context, and match financial and clinical data in ways that separate systems simply cannot support.
5. Clinical Research Prebuilt FHIR pipelines and OMOP transformations reduce the research data preparation cycle by months. The University of Wisconsin-Madison School of Medicine and Public Health, which manages $524 million in annual extramural research funding, is using Fabric to build a Colorectal Cancer Multi-Modal Data Commons that unifies clinical, imaging, and genomics data for advanced research. Microsoft’s community hub also provides detailed guidance on building research data platforms in Fabric, including patterns for cohort discovery, IRB workflows, and multi-modal data curation.
6. AI and Advanced Analytics EPAM, a Microsoft Cloud for Healthcare partner , reported that using Fabric’s healthcare data solutions resulted in more than 40% reduction in implementation time and costs for a recent AI and advanced analytics project. The pre-built data foundation eliminated much of the custom engineering that would otherwise have been required to prepare healthcare data for machine learning and generative AI workloads.
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Compliance and Security in Fabric for Healthcare In healthcare, analytics platforms are judged as much on trust as on capability. Any system handling clinical or patient data must meet strict privacy, security, and governance requirements from day one. Microsoft built Fabric with these constraints in mind, making compliance part of the platform rather than a separate layer to manage.
How Fabric Supports Healthcare Compliance Built-in readiness for HIPAA and GDPR requirements Deep integration with Microsoft Purview for data governance , lineage visibility, and classification Role-based access control to limit data access by role, team, or responsibility Data sensitivity labels to identify and protect regulated informationData masking and encryption for data both at rest and in transitWorkspace-level isolation to separate departments, projects, or research initiatives
Together, these controls allow healthcare organizations to enable analytics across teams while maintaining strict oversight. Clinical, operational, and research users can work from the same platform without increasing compliance risk or data exposure.
How Fabric’s Architecture Supports Healthcare Data at Scale Healthcare data grows quickly and comes from many sources, which makes scalability a core requirement rather than a future concern. Microsoft Fabric is built to handle large, diverse datasets while keeping analytics workflows consistent and manageable.
Key Architectural Elements Medallion Architecture that organizes data as it moves from raw ingestion in Bronze, to cleaned and validated data in Silver, and analytics-ready data in GoldOneLake as a single shared data foundation, removing the need to copy data between servicesData Factory with native connectors for EHR systems, Azure Health Data Services, and third-party sourcesServerless SQL that scales automatically for analytics workloads without infrastructure provisioningPower BI for self-service reporting across clinical, operational, and financial teams
This architecture allows healthcare organizations to scale analytics step by step. As new data sources are added or workloads increase, teams continue to work from the same governed data foundation without rebuilding pipelines or managing additional infrastructure.
Source: Microsoft Case Study 1: Kanerika’s Migration Accelerators for Pharma and Healthcare Challenge A healthcare and pharma organization relied on legacy BI tools that slowed clinical and operational reporting. Teams struggled with delayed insights because data was spread across Crystal Reports , SSRS, and Tableau. Leadership needed faster reporting, better visibility, and a smoother path to Microsoft Power BI and Microsoft Fabric without long or risky migrations.
Solution Kanerika used its migration accelerators to move legacy BI workloads into Microsoft Power BI and Microsoft Fabric. The approach cut manual migration work and unified data into one platform. Automated conversion steps helped the client shift without disrupting day-to-day operations. This created a single analytics environment with improved access and governance.
Results 71% higher reporting accuracy 38% lower data handling costs 64% faster decision-making across clinical and business teams Clearer and more compliant data access across the organization
Challenge A healthcare provider had fragmented systems for clinical records, workflows, and billing. Manual processes slowed reporting and increased the cost of managing data. The organization wanted to improve accuracy, speed, and shift toward proactive care with AI-supported insights.
Solution Kanerika introduced AI-powered analytics and workflow automation . The team improved EHR optimization, automated key clinical and operational tasks, and set up predictive analytics for patient outcomes. Additionally, interoperability improvements connected data across departments, giving clinicians and administrators a unified view.
Results
Kanerika Supporting Enterprise Growth through Microsoft Fabric Kanerika is a Microsoft Data and AI Solutions Partner that helps enterprises build reliable data systems on Microsoft Fabric. Our work comes from real implementations where teams need stronger analytics, smoother engineering, and clearer reporting. This gives us hands-on understanding of Fabric architecture, AI features, and unified analytics .
We shape each solution around what a company needs from its data. Some teams want faster decisions based on real-time information. Others need better business intelligence or support for large datasets. We build models, pipelines, and dashboards that use the full Fabric platform with Spark-based engineering, OneLake storage, shared compute, and the wider Microsoft ecosystem. However, we always keep the design simple so teams can use their data without friction.
Kanerika also supports automated migration to Fabric through our FLIP-based approach. It reduces manual work and helps organizations shift without slowing down daily operations. Additionally, our steady delivery method covers architecture design, semantic modeling , governance, and user support. Therefore, teams adopt Fabric faster, keep their data secure and see clear business results with less effort.
FAQs How does Microsoft Fabric support healthcare analytics? Microsoft Fabric helps healthcare organizations bring data from EHRs, claims, imaging systems, and other sources into one analytics platform. Using OneLake and prebuilt healthcare pipelines, teams can prepare and analyze data faster without building custom integrations for every use case. This makes it easier to get a unified view of clinical, operational, and financial data.
Can Microsoft Fabric be used for healthcare data compliance? Yes, Microsoft Fabric supports healthcare compliance needs through built-in security and governance. It includes role-based access control, encryption for data at rest and in transit, and integration with Microsoft Purview for data governance and lineage. These features help organizations work with sensitive healthcare data securely.
What is Microsoft Fabric used for? Microsoft Fabric is a unified analytics platform streamlining data integration, analysis, and visualization. It simplifies the entire data lifecycle, from ingestion to reporting, eliminating the need for multiple, disparate tools. Essentially, it’s a one-stop shop for all your data needs, empowering faster insights and better collaboration. It replaces the need for piecing together various solutions.
How can Microsoft be used in the healthcare industry? Microsoft’s cloud services (Azure) securely store and analyze massive healthcare datasets, improving patient care through predictive analytics. Its Power Platform empowers efficient workflows and data management for hospitals and clinics. Furthermore, Microsoft Teams facilitates secure communication and collaboration among medical professionals, enhancing teamwork and patient outcomes. Essentially, Microsoft provides the digital infrastructure and tools to modernize and optimize healthcare delivery.
What is the main use of Microsoft Fabric? Microsoft Fabric is a unified analytics platform designed to streamline your entire data journey. It combines data ingestion , transformation, storage, analysis, and visualization into one cohesive service, eliminating the need for multiple disparate tools. This simplifies data management and analysis, making insights more accessible to everyone from business analysts to data scientists. Ultimately, it aims to accelerate data-driven decision-making within organizations.
Is Microsoft Fabric similar to Databricks? Microsoft Fabric and Databricks both offer cloud-based data analytics platforms, but they target different needs. Fabric is a more integrated, end-to-end solution encompassing data warehousing, analytics, and real-time processing within a unified experience. Databricks, while versatile, focuses primarily on Spark-based data engineering and analytics , often requiring more integration with other tools for a complete solution. Essentially, Fabric aims for simplicity and all-in-one functionality, while Databricks prioritizes advanced analytics capabilities and customizability.
Why do I need Microsoft Fabric? Microsoft Fabric simplifies your data journey, unifying data integration, engineering, warehousing, analytics, and real-time insights into one powerful platform. It eliminates the need for juggling multiple tools and reduces the complexity of data management , allowing you to focus on deriving valuable business insights faster. This unified approach minimizes data silos and improves collaboration across your organization. Essentially, it streamlines your entire data workflow for greater efficiency and actionable intelligence.
Is Microsoft Fabric a PaaS or SaaS? Microsoft Fabric blurs the traditional PaaS/SaaS lines. It’s best described as a unified analytics platform *delivered* as a SaaS, but offering many PaaS-like capabilities for customization and control within its environment. Think of it as a SaaS with a powerful, customizable PaaS core. Ultimately, the user experience is predominantly SaaS.
