Credit Union
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Large US Credit Union Selects Cohesity for Next-Gen Data Management with Improved Security

Industry

Finance

Region

Americas

Use Cases
  • Backup and Recovery
  • Disaster Recovery
  • File and Object Services
Products
  • DataProtect
  • SmartFiles
Industry

Finance

Region

Americas

Use Cases
  • Backup and Recovery
  • Disaster Recovery
  • File and Object Services
Products
  • DataProtect
  • SmartFiles

99%

Reduction for file share backup

“The importance of using the same vendor for our backup and file and object services can’t be understated. By offering a complete and powerful solution for both environments, Cohesity significantly improves our ability to protect and secure our valuable data, simplifies system management, and streamlines ongoing support.”

Gurdeep, Senior Systems Engineer, Large US Credit Union

At a Glance

Cohesity has greatly improved the ability to back up data quickly and recover from any potential data breaches. Cohesity’s data management platform provides a single view of all data and applications. Moving away from Veritas NetBackup and the tape backup environment to Cohesity was very cost effective.

Challenge

The credit union was relying on an aging Veritas NetBackup implementation, along with Dell EMC Isilon NAS storage systems. Both environments were due for a refresh, and the company needed additional capacity for several new customer-facing banking services, back-office applications, and other financial systems.

Solution

The large credit union implemented Cohesity DataProtect for backup and recovery, as well as Cohesity SmartFiles for file and object services.

Result

By moving to Cohesity, the credit union was able to improve data security, reduce its backup windows for the department file share by over 99%, cut IT management time by over 65%, and save over $10K per month by migrating off of tape backups.

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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