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Healthcare Cloud Data Migration Challenges Organizations

Healthcare cloud data migration is an inevitable, but challenging step to advanced IT infrastructure.

Healthcare cloud data migration

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- Healthcare cloud data migration challenges most organizations that are upgrading their IT infrastructure to include more advanced solutions. As health IT infrastructure technology continues to evolve, clinical data is outliving the devices and methods used to store them.

The healthcare industry is currently in the midst of a cloud mass migration. A recent report shared by Reportlinker predicts the cloud migration services market to grow at a CAGR of 24 percent through 2021.

Report authors stated that recent wide-spread cloud calls for the migration of enterprise applications, infrastructure tools, and business processes to the cloud. Migrating clinical data consists of a variety of complications, including service interruptions and service delays that make cloud migration service selection a vital part of the migration process.

Currently, healthcare organizations are dealing with legacy on-premise storage systems that are expensive to expand and maintain. More organizations are moving to the cloud, but entities are also faced with the challenge of how to best execute a data migration.

While most healthcare organizations maintain a partial on-premise storage deployment for some data, healthcare entities are using cloud in some capacity.

Late last year, a SADA Systems survey reported that 89 percent of healthcare organizations are currently using cloud-based health IT infrastructure, and the vast majority of providers are likely to increase their investment in these tools over the next few years.

With each now infrastructure cloud adoption, a migration needs to take place. Some migrations are relatively minor but every organization will face a large data migration at some point.

Moving data on a large scale is a serious undertaking that involves proper prior planning to ensure the data will be safe every step through the transition. Organizations migrating clinical data to the cloud need to consider the following:

  • Systems cannot move an entire data repository at once because of hardware and network restrictions.
  • Some data may not be accessible during migration.
  • Leaving data in a transitional state can heighten the risk of major data loss.

Migrating clinical data to the cloud is a massive commintment for healthcare organizations of every size, and several vendors are offering collaborative services to ensure entities are making a smooth and guided transition to the cloud.

Earlier this year, Actifio announced its support of Microsoft Azure cloud migration. The data virtualization company supports Microsoft Azure via Actifio Sky to enable instant data recovery across data centers and cloud-based infrastructure.

Actifio’s data virtualization platform leverages Microsoft Azure for their mission-critical applications. The copy data virtualization platform speeds up the migration process. It does this by accelerating hybrid cloud adoption for test data provisioning for application development, backup, disaster recovery, instant recovery, data migration, long-term retention or analytics.

"The move to cloud is a fundamental shift that allows IT leaders to break free from 20-year old mindsets, backup tools, and siloed approaches to data management that burden Ops and Dev teams and restrict agility between data centers and Cloud," Actifio CEO and Founder Ash Ashutosh said in a statement.

"Data and particularly databases in Microsoft Azure need to be available on-demand, instantly, via an API, not stuck in an archaic backup format,” Ashutosh continued. “Actifio copy data virtualization is allowing our customers to get their data into Azure, build SQL-as-a-service capabilities to speed up their development pipelines and satisfy board-level requirements for rapid disaster recovery."

Cloud data migration is necessary to replace legacy on-premise systems. Organizations are making the change to save on future data storage costs by eliminating servers wherever possible and embracing more flexible and scalable data access.