The artificial intelligence revolution is supposed to bring an age of groundbreaking innovation for businesses, yet 63% can’t seem to reach their AI goals without major improvements or a complete overhaul of their data storage. Without an intelligent data infrastructure, deploying and scaling AI can be complicated. Let’s look at these challenges and consider how unified data storage can help.
AI begins and ends with data. AI datasets span a wide range of locations; businesses capture diverse and multimodal datasets across edge, core, and cloud within an AI lifecycle. Understanding where your data lives and how to best manage, consolidate, and classify it becomes difficult when you’re trying to manage workflows across disconnected environments full of silos and disparate tools. IT teams need enterprise AI solutions that provide a seamless, hybrid workflow that they can manage through a single control plane.
The complexities of AI data storage have propelled NetApp to reimagine what unified data storage can do, with the aim of making it easier for businesses to handle their AI landscape. When you simplify AI data management with a unified control plane and a single-storage operating system, it’s easier to provision data to users, AI developers, and applications across any hybrid multicloud environment. You also benefit from efficient data mobility to adapt more easily to the breakneck pace of AI. The result is a more streamlined and efficient AI data pipeline.
When it comes to AI, massive datasets are in constant motion between on premises and major public clouds across every stage of processing. Roadblocks and bottlenecks slow down productivity, and valuable insights can fall through the cracks. No data scientist, engineer, or developer wants that, so they end up spending costly hours trying to navigate through unwieldy processes instead of focusing on what matters: the data and the company’s AI goals.
When you build an intelligent data infrastructure, you’re able to overcome the AI data storage challenges that come from less integrated systems. Remove the bottlenecks and give the IT teams all the performance, efficiency, and scale they need to start maximizing productivity, operations, and GPU utilization. Only then can your business successfully accelerate the data pipeline and scale AI across the entire enterprise.
With responsible AI come governance, policies, and regulations. If your data security fails and your IP slips into public large language models, or if you experience one of the many cyberthreats, your AI project will grind to a halt. Any outside or unnecessary impact – AI runtime manipulation, poisoned training data, model theft – can jeopardize the best intentions. Violations of data security policies are a real risk, which is why companies need built-in data governance and security.
IT teams can deploy and scale AI confidently, knowing that the NetApp® approach to unified data storage has built-in anomaly detection to spot and mitigate risks. Turnkey, trusted, and secure, these robust enterprise AI solutions mean that teams can leverage the right data while complying with internal policies and local regulations.
In short, unified data storage can help your data infrastructure easily adapt to AI workloads. NetApp can help resolve AI data management complexities and amplify productivity, while ensuring regulatory compliance.
“NetApp AIPod consolidates a data center’s worth of analytics, training, and inference computing into a single, integrated system. We can easily get our AI and machine learning workloads up and running without worrying about setting up our own AI infrastructure.”
– Anri Kitami, software Engineering Specialist, Pong Yuen
NetApp’s approach to unified data storage can help you conquer the challenge of powering your entire AI pipeline. Drive any data type, any workload, across any hybrid cloud environment with a single data management experience. No more silos, no more storage complexity—just powerful, intelligent, secure storage to accelerate your business. Learn more about NetApp enterprise AI solutions.
Jason is a business and marketing professional with over 20 years of product marketing, product management, and corporate finance experience. Since joining NetApp in 2008 he has been focused on SAN and NAS storage, backup and disaster recovery solutions, and cloud data services. When not in the office, you can find him cycling, cooking, enjoying time with family, and volunteering at his church and in the community.