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HNL Achieves ROI in 12 Months, Adds Protection to Microsoft 365 with Agile Dev/Test

Industry

Healthcare

Region

Americas

Use Cases
  • Backup and Recovery
  • Cloud
  • Dev/Test
Products
  • DataProtect
Industry

Healthcare

Region

Americas

Use Cases
  • Backup and Recovery
  • Cloud
  • Dev/Test
Products
  • DataProtect

50%

reduction in footprint

“Cohesity is integral to our everyday operations. It’s an efficient, simpler way to provide long-term backups for Microsoft 365, objects, and other workloads to meet our retention requirements, and using it for agile dev/test speeds our time to market.”

Harvey Guindi, Chief Information Officer, HNL Lab Medicine

At a Glance

HNL Lab Medicine recognizes that 70 percent of medical decisions are made using data that comes from laboratory medicine services like its own. A key factor in HNL’s decision to select Cohesity was that it was built for on-prem and cloud to do so much more than traditional backups.

Challenge

After a multi-year modernization of its data center to a Nutanix-based hyperconverged infrastructure was complete, HNL’s legacy backup solution needed to be overhauled or replaced entirely. The company faced a costly, forklift upgrade of its legacy Veeam system to make it fit into the new, security-conscious, software-driven environment.

Solution

HNL uses Cohesity to simplify and boost its traditional workload, objects, and Microsoft 365 data protection — which encompasses the SaaS-based productivity apps as well as SharePoint, Teams, and OneDrive data — as the lab moves away from traditional NAS infrastructure.

Result

Since deploying Cohesity as its modern data management platform, HNL staff can take on additional work because less time is required to manage backups. HNL also has accelerated the time to market of critical apps  and achieved 100 percent ROI in less than 12 months.

Related Products

Simplify your data management for backups, file shares, object stores, dev/test, and analytics.

Related Solutions

The smarter, simpler way to solve mass data fragmentation.

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