Bringing New Innovations to Today’s Data-First Storage Modernization Strategies
File data is the innovation engine of business today. One only has to think of the advances brought on with genetic sequencing, modeling, simulations, medical imaging technology (PACS), diagnostic imagery, surveillance, or even group shares and home directories to grasp the sheer value to be unlocked by the zettabytes of unstructured data now in creation. According to IDC, global data creation and replication will experience a compound annual growth rate (CAGR) of 23% by 2025.
For some organizations, successfully leveraging their data is about developing next-gen operating and business models, delivering a rich experience, or accelerating decision velocity. At HPE we refer to this as data-first modernization.
The Key to Unlocking Your Data’s Value
But, while an organization can understand that data is its life force, it’s not always easy to derive value out of it. Why? Data is in disarray, spread across organizational silos, or trapped in legacy systems that you are not yet monetizing. There’s also volumes of it being created at the edge, beyond what you can handle. And, if that weren’t enough, there’s also the tremendous headache associated with the migration of apps and data.
Put simply, the unstructured data explosion has resulted in a storage management nightmare. Organizations are producing massive amounts of unstructured file data that needs to be stored, managed, protected and analyzed, but legacy architectures that were created 20 years ago can no longer keep up with growing demands. These organizations are looking for the power, scale, and cost-efficiency that comes with cloud, but multi-gen IT is here to stay and hindering their data-first modernization.
Regardless, public cloud is not a cure-all for well-documented reasons, such as vendor lock-in, data movement/egress charges, data sovereignty, and security issues. Likewise, organizations that depend on rapidly growing, data-intensive workloads—being highly accessible—must have the capacity they need, when they need it.
Modernizing Your Data-First Strategy
As part of their data-first modernization strategy, organizations should instead focus on adopting a data-central mentality and philosophy that drives a unified experience and increases decision velocity, while keeping control of their data assets. To address these needs, HPE GreenLake with Qumulo provides a self-service, pay-as-you-go file platform for unstructured data. HPE GreenLake with Qumulo simplifies IT operations, eliminates data blindness, and delivers cloud-scale economics on-premises or in an organization’s colocation facilities. This allows you to fast forward your multi-gen IT, while injecting dynamic scalability and enterprise-level security and data protection across the edge to your datacenter and the cloud.
An Innovative Vision Brings Data to Life
Auckland Transport (AT) is responsible for all of the region’s transport services including footpaths, public transport, and parking. The agency uses a network of video cameras around the city to monitor the comings and goings of people and vehicles through a unified dashboard to optimize transport routes. It also makes its AI-enhanced video feed available to support emergency services and law enforcement, keeping citizens safer. This characterizes the trend in video surveillance storage, encompassing the growing number of cameras, resolution required, and the need to retain data for longer. The dynamic scalability of Qumulo combined with control and pay-as-you-go economics of the HPE GreenLake edge-to-cloud platform provided the ideal service to meet these needs. HPE GreenLake with Qumulo has proven integration with leading video management systems (VMS) providers to enable Auckland Transport to achieve their goals.
- Solution page: Read more about Qumulo and HPE
- Solution brief: HPE GreenLake with Qumulo’s File Data Platform (PDF)
- Related story: Flexible Capacity at Scale with Qumulo on HPE GreenLake Cloud Services
Enable Peak Performance with HPE All-NVMe and Qumulo
Enterprises depend on applications that are running business-driving analytics, training machine learning models, rendering animation, analyzing machine data, doing genomic research, and much more. Download this ESG Technical Review to view results of remote testing of the Qumulo File Data Platform.Download the Playbook