Integrated Healthcare System Saves $5M, Avoids Lock-In with Komprise Cloud Tiering
Healthcare IT team has tiered more than 6PB to Azure Blob with plans to continue moving data over time. This is freeing up significant space on its on-premises storage arrays
and avoiding millions of dollars on storage and backup refresh costs.
A U.S.-based academic healthcare system with several hospitals and a medical school faced the same data challenges every other healthcare group today is dealing with: rapid growth of large medical image files and research data, which constrain IT resources, who are required to store, protect and manage at a huge cost. This unstructured data is highly strategic to healthcare organizations. It can be used to drive cutting-edge research, patient-centric care and more efficient practices. But is an enormous expense and burden to manage.
Read this case study to learn how analytics-driven unstructured data management approach, the storage team is now using Komprise to tier cold data to Azure. So far, IT has tiered more than 6PB to Azure Blob with plans to continue moving data over time. This is freeing up significant space on its on-premises storage arrays and avoiding millions of dollars of unnecessary storage and backup refresh costs.
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FAQs
Why is unstructured data management such a costly problem for hospitals and integrated healthcare systems?
Hospitals and integrated healthcare systems are among the most data-intensive organizations in any sector. Clinical notes, medical imaging, lab results, sensor readings, patient records, and operational data accumulate continuously, and the overwhelming majority of it is unstructured data, meaning it cannot be easily organized, searched, or acted on without the right tools in place.
The financial pressure is compounding. Every year, that data must be stored, protected, backed up, and kept compliant, regardless of whether it is ever accessed again. Most of it never is. Meanwhile, primary storage arrays fill faster than budgets allow, forcing IT teams into repeated refresh cycles that consume capital without solving the underlying problem. The result is a system where the data that should power better patient care and AI-driven research instead becomes one of the largest line items in the IT budget.
According to the World Economic Forum, a typical hospital produces 50 petabytes of data per year, and 97% of it goes unused. That is not a data shortage. That is an unstructured data management problem.
Source: World Economic Forum, “How to harness health data to improve patient outcomes,” January 2024
What unstructured data management use cases matter most for hospitals and healthcare systems?
Several use cases surface consistently across hospital and integrated healthcare system environments:
- Primary storage capacity relief: Medical imaging alone can consume petabytes of premium flash and NAS estates. Identifying cold, stale, and duplicate files and tiering them to lower-cost cloud object storage, without disrupting clinical workflows, is often the first and highest-value priority. See ROT data.
- Avoiding storage and backup refresh costs: Hardware refresh cycles represent significant capital expenditure. Organizations that tier data off primary storage before a refresh can dramatically reduce the capacity they need to replace or expand, avoiding millions in unnecessary spend.
- Cloud tiering without lock-in: Many healthcare IT teams are cautious about cloud adoption because of concerns about vendor lock-in and egress costs. A storage-agnostic tiering approach lets organizations move data to cloud object storage, including Azure Blob, while preserving the ability to move it again as costs and contracts change.
- Sensitive data governance and HIPAA compliance: Patient data carries strict retention and access requirements. Understanding what data exists, where it lives, and who can access it is a prerequisite for compliance — and for reducing exposure in the event of a breach or audit.
- AI data preparation: Healthcare AI pipelines need governed, curated datasets. Smart Data Workflows can classify and route clinical and research data to AI systems automatically, with full audit trails, without requiring changes to how clinicians or researchers access their data.
How did this integrated healthcare system save millions and avoid storage lock-in?
The healthcare system faced a challenge familiar to most large hospital organizations: rapid growth in medical imaging and research data was filling primary NAS arrays faster than IT could manage, driving pressure to purchase additional hardware or commit to long-term vendor contracts.
Rather than refresh aging storage arrays or lock into a single cloud provider, the IT team used Komprise to analyze what data existed across their environment, identify cold and infrequently accessed files, and tier that data to Azure Blob storage. Transparent Move Technology preserved native file access paths throughout, so clinical staff and researchers experienced no disruption.
The result was more than 6 petabytes of data tiered to Azure Blob, millions of dollars in storage and backup refresh costs avoided, and no vendor lock-in. The team retains the flexibility to move data to a different cloud or storage tier as needs and pricing evolve.
Read the customer case study: Integrated Healthcare System Saves $5M, Avoids Lock-In with Komprise Cloud Tiering
What makes Komprise the right choice for healthcare unstructured data management?
Healthcare IT environments face a set of constraints that most data management tools are not built for: strict compliance requirements, zero tolerance for clinical workflow disruption, multi-vendor storage environments, and the need to demonstrate ROI quickly to budget-conscious leadership.
Komprise addresses each of these directly:
- Non-disruptive by design: Transparent Move Technology moves data off primary storage without breaking file paths or changing how clinical applications, imaging systems, or researchers access their files. There is no rip-and-replace, no downtime, and no change management burden on clinical staff.
- No vendor lock-in: Komprise is storage agnostic. Data can be tiered to Azure, AWS, Google Cloud, or any supported object store, and moved again as contracts or requirements change. Healthcare organizations are never tied to a single cloud provider.
- Compliance and governance built in: Automated sensitive data detection helps teams find and govern regulated patient data across petabytes, supporting HIPAA retention requirements and audit readiness without manual processes.
- AI-ready: Smart Data Workflows and KAPPA data services enrich and route clinical and research data to AI pipelines automatically, with governance and audit trails, giving healthcare AI teams the governed datasets they need without manual data preparation.
The healthcare data storage market is projected to grow from $5.4 billion in 2024 to more than $15 billion by 2032, driven by rising data volumes and increasing regulatory demands. Organizations that manage their unstructured data strategically will convert that growth from a cost burden into a clinical and competitive asset.
Source: SNS Insider, “Healthcare Data Storage Market Size and Forecast,” 2024
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