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“IDC estimates that by 2020, organizations that are able to analyze all relevant data and deliver actionable information will achieve an extra $430 billion in productivity benefits over their peers,” IBM continued in its statement. “As the volume of data grows rapidly, enterprises require higher levels of performance and efficiency to quickly and easily generate these valuable insights.”
IBM’s Cloud Infrastructure Services General Manager John Considine said that the upgrades to the bare metal servers was driven by the need for organizations to fully harness their data for better decision-making and transformative growth. Organizations need to generate better value from their data.
The Intel Xeon Scalable processors will help organizations run high performance computing workloads, including genomic analysis and other demanding healthcare big data workloads. According to Intel, the new processors will accelerate data insights up to 1.7 times faster for life science workloads.
Healthcare organizations can benefit greatly from accelerated data processing so they can have access to patient results at the point of care. This reduces readmissions and follow up appointments to examine results.
The bare metal deployments install the virtual machine directly onto the hardware instead of the server’s operating system.
IBM’s new bare metal deployment also provides a dedicated and secure environment that can be customized to meet an organization’s unique needs. The IBM cloud also gives organizations access to over 160 application programming interfaces (APIs), analytics software, blockchain, and IoT.
The solution also uses graphics processing units (GPUs) for cognitive and high performance computing. GPUs are becoming more popular for big data analytics as organizations demand more speed.
The GPU is part of the CPU and was originally created for 3D game rendering, but its capabilities extend beyond image rendering. It was discovered that GPUs are more efficient than CPUs because they can process large blocks of data.
Healthcare organizations are turning to more advanced data center technology because of the big data analytics demands on IT infrastructure. Organizations are also seeking computing power that will allow them to embrace real-time analytics.
Real-time analytics lets clinicians collect, analyze, and decide on a patient’s condition during their initial interaction. Real-time environments lower costs because organizations can avoid bulk processing and the overnight loading into data warehouses.
Real-time environments also help with data governance, making sure the information entered is correct. If organizations can address data governance upfront, then it solves a lot of problems concerning data quality.
A survey conducted last year by OpsClarity stated that healthcare providers and life science companies are among the 92 percent of cross-industry organizations that plan to invest in near real-time big data analytics applications as soon as possible.
A virtualized approach supports real-time analytics, which is why bare metal servers are gaining popularity in healthcare. Real-time analytics support value-based care incentives because they reduce costs by lowering the number of patient visits by providing results in real-time.
Clinicians with access to real-time data have a smaller chance of misdiagnosing the patient because they are better advised at the point of care.
Healthcare organizations exploring big data analytics need to ensure that they have invested in tools that will support the heavy workloads and enable them to seek more advanced technology in the future.
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