Cost Savings of IBM Cloud Pak for Data on Red Hat OpenShift
Improve ROI with IBM Cloud Pak for Data System
IBM Cloud Pak for Data System is a hyper-converged inter-operable platform that provides software defined network, storage and compute to reduce complexity, increase scalability, and accelerate time to value. It helps maximize ROI can significantly reduce the Total Cost or Ownership (TCO) for clients in their analytics/AI journey.
Infrastructure savings of IBM Cloud Pak for Data on Power Systems
Power Systems are ranked #1 in every major reliability category and deliver the most reliable on-premises infrastructure to meet around-the-clock customer demands. Cloud Pak for Data on Red Hat OpenShift deployed on Power Systems allows you to easily integrate with your organization’s private or hybrid cloud strategy. It provides the foundation for executing AI workloads using GPU-accelerated POWER 9 technology. With Power Systems, clients can take advantage of superior core performance and memory bandwidth to deliver both performance and price-performance advantages.
Flexible platform: Land and expand or plug and play architecture
- Containers and container management efficiencies totaling USD 12.5 million to USD 14.4 million. With Cloud Pak for Data, companies can improve their readiness for cloud migration, improve licensing flexibility with IBM, and reduce both hardware purchases and infrastructure management efforts.
- Based on the customer interviews, Forrester modeled the financial impact for the composite organization with the following estimates:
- The composite organization has 10 data stores located in different countries.
- For each data store, there are three IT FTEs responsible for managing the infrastructure. With Cloud Pak for Data, the composite expects to reduce that effort by between 65 percent to 85 percent, which allows the IT FTEs to spend more time on higher value tasks (e.g., innovation).
- A third of the composite organization’s servers are refreshed annually. Due to an increase in hardware utilization, the composite expects to reduce the amount of hardware purchases by 33 percent during each refresh cycle.
This yields a three-year projected PV ranging from USD 12.5 million to USD 14.4 million. The summary table for the low, mid, and high projections is shown below, followed by the detailed calculations for each projection.
As you embark on your data architecture modernization, choose a solution that not only provides you with a flexible infrastructure, but one that helps you reduce costs while accelerating business insights. Take the next steps by signing up for our webinar on June 23 joined by our guest, Forrester analyst speaker, to learn more on the benefits of a unified data and AI platform.
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