At the NYSE, theCUBE Research’s Dave Vellante sits down with Darren Miller, technical staff member for unstructured data storage at Dell Technologies, and Matheen Raza, principal product marketing manager at Nvidia, for a conversation about how these two tech giants are reshaping enterprise AI. They explore how storage and accelerated computing are converging to make large-scale AI more efficient and accessible.
Dell’s unstructured data solutions are helping organizations manage the explosion of AI-generated data, Miller explains. Nvidia’s AI platform certifications bring confidence and performance optimization to enterprise deployments, Raza expands. Together, they unpack how integrating smart storage with accelerated computing is redefining data center design and AI readiness.
The discussion highlights Dell and Nvidia’s co-engineered reference designs — including the Nvidia AI Data Platform and Dell’s PowerScale RAG connector — built to streamline AI workloads. These technologies transform data centers from cost centers to value generators, accelerating innovation, strengthening data governance and unlocking intelligent, scalable AI operations across industries, they both emphasize.
Forgot Password
Almost there!
We just sent you a verification email. Please verify your account to gain access to
Dell AI Data Platform Event. If you don���t think you received an email check your
spam folder.
In order to sign in, enter the email address you used to registered for the event. Once completed, you will receive an email with a verification link. Open this link to automatically sign into the site.
Register for Dell AI Data Platform Event
Please fill out the information below. You will receive an email with a verification link confirming your registration. Click the link to automatically sign into the site.
You’re almost there!
You are now verified for the Dell AI Data Platform event! You now have access to our resources and can save the date of the broadcast using the "Add to Calendar" button.
I want my badge and interests to be visible to all attendees.
Checking this box will display your presense on the attendees list, view your profile and allow other attendees to contact you via 1-1 chat. Read the Privacy Policy. At any time, you can choose to disable this preference.
Select your Interests!
add
Upload your photo
Uploading..
OR
Connect via Twitter
Connect via Linkedin
EDIT PASSWORD
Share
Forgot Password
Almost there!
We just sent you a verification email. Please verify your account to gain access to
Dell AI Data Platform Event. If you don’t think you received an email check your
spam folder.
In order to sign in, enter the email address you used to registered for the event. Once completed, you will receive an email with a verification link. Open this link to automatically sign into the site.
Sign in to gain access to Dell AI Data Platform Event
Please sign in with LinkedIn to continue to Dell AI Data Platform Event. Signing in with LinkedIn ensures a professional environment.
Are you sure you want to remove access rights for this user?
Details
Manage Access
email address
Community Invitation
Storage That Fuels Breakthroughs: Dell + NVIDIA for AI
At the NYSE, theCUBE Research’s Dave Vellante sits down with Darren Miller, technical staff member for unstructured data storage at Dell Technologies, and Matheen Raza, principal product marketing manager at Nvidia, for a conversation about how these two tech giants are reshaping enterprise AI. They explore how storage and accelerated computing are converging to make large-scale AI more efficient and accessible.
Dell’s unstructured data solutions are helping organizations manage the explosion of AI-generated data, Miller explains. Nvidia’s AI platform certifications bring confidence and performance optimization to enterprise deployments, Raza expands. Together, they unpack how integrating smart storage with accelerated computing is redefining data center design and AI readiness.
The discussion highlights Dell and Nvidia’s co-engineered reference designs — including the Nvidia AI Data Platform and Dell’s PowerScale RAG connector — built to streamline AI workloads. These technologies transform data centers from cost centers to value generators, accelerating innovation, strengthening data governance and unlocking intelligent, scalable AI operations across industries, they both emphasize.
Storage That Fuels Breakthroughs: Dell + NVIDIA for AI
Darren Miller
Director, Technical SolutionsDell Technologies
Matheen Raza
Product Marketing Lead, Enterprise AINVIDIA
At the NYSE, theCUBE Research’s Dave Vellante sits down with Darren Miller, technical staff member for unstructured data storage at Dell Technologies, and Matheen Raza, principal product marketing manager at Nvidia, for a conversation about how these two tech giants are reshaping enterprise AI. They explore how storage and accelerated computing are converging to make large-scale AI more efficient and accessible.
Dell’s unstructured data solutions are helping organizations manage the explosion of AI-generated data, Miller explains. Nvidia’s AI platform ...Read more
exploreKeep Exploring
What is Dell's approach to data management?add
What are the collaborative efforts between Dell and NVIDIA in relation to their AI platforms?add
What challenges are enterprises facing when building and utilizing RAG pipelines, and what solutions are being developed to address these issues?add
Storage That Fuels Breakthroughs: Dell + NVIDIA for AI
search
Dave Vellante
>> Hi everybody, this is Dave Vellante. We're here at the New York Stock Exchange for a very special CUBE conversation. Really appreciate you joining us today where we're exploring how two key companies in the AI era, NVIDIA and Dell, are working together to really more rapidly accelerate AI across enterprises and specifically the role that storage engines play in doing so. A lot of times people forget about the data and the storage, so I want to dive right in. Darren Miller is here. He is the technical staff member for unstructured data storage, that's where all the action is in AI, over at Dell Technologies. And Matheen Raza is a product marketing lead for enterprise AI at NVIDIA. Gentlemen, thanks for coming in remotely. I wish you were here face to face, but really a pleasure to have you.
Matheen Raza
>> Thank you.
Darren Miller
>> Thanks Dave.
Dave Vellante
>> You bet. All right.
Darren Miller
>> Happy to be here.
Dave Vellante
>> Let's get into the role of data in AI and storage, the impact that that plays. And Darren, as we always talk about AI, it's only as good as the data that serves it, that powers it. Jeff Clark had a very spicy statement this past year at DTW to that regard. You got to deliver it rapidly, efficiency. How do you describe Dell's approach to data management?
Darren Miller
>> Sure, Dave, so you mentioned Dell's storage engine and PowerScale is one of the four platforms of Dell's AI storage engine. When you think about Dell's data management approach, it's really an approach of three pillars of place protect and process. And essentially, what that means is we help you place your data on high-performance, powerful storage systems, and then that allows these different AI workflows to then process that data for depending on whether the workflow is a rag workflow or training or fine-tuning, whatever it might be, and then ultimately, enabling protection of that data so that you have essentially that total data lifecycle. If you think of how we're doing this with NVIDIA, one of the things that we've been working really hard at is to continue to produce reference designs co-developed by Dell and NVIDIA based on the NVIDIA different AI platforms that they're serving, such as SuperPOD, enterprise storage certifications, as well as NCP, which is NVIDIA's cloud partner program. So, we've really been involved in bringing our storage to those platforms and those programs, help build confidence for customers that want to run large scale AI infrastructures.
Dave Vellante
>> Thank you for that, Darren. Matheen, NVIDIA obviously is leading the AI charge. You've got a highly well thought out integrated stack, and so from your perspective, you've got to certify the solutions for customers. You've got the NV cert program. What does that mean for storage providers and specifically, what's the value for customers?
Matheen Raza
>> Yeah, definitely. Let me talk a little bit about this and let me take a step back and talk about this concept of AI factory or AI factories. As enterprises are building AI workloads and experimenting with AI, we see this need for rethinking how a data center is built and how a data center is operated with the rise of. We see every different workload is going to get accelerated and enterprises need to start looking at these data centers not just as a cost center where you're running your applications, but as an engine that takes data and electricity as inputs and delivers output as token. And these tokens are then, these are the intelligence that you're delivering to your end users or your internal customers that eventually deliver business value. I talked about the AI factory and the concept, but there's a variety of different AI factories. You could have an AI factory that's focused on large scale training, large scale inference, and there's the enterprise AI factory that's supporting a variety of different accelerated computing workloads. But in each of these, one of the key inputs to an AI factory is data. And of course, with this, we also see needs for new integrations and we communicate those integrations as part of our reference architectures and partners such as Dell take those components and innovate on their end and build out these solutions for end customers.
Dave Vellante
>> I think the point you made Matheen is key because 10, 15 years ago, everybody was saying, let's get rid of the data center. It's a cost center, and you're talking about turning it into a profit center. We wrote a piece at theCUBE research recently, Jensen's new law, buy more, save more. It actually talked about where power is a constraint and network utilization is low, you can actually monetize in a new way. So, it's a completely different mindset when you bring in extreme parallel processing or what you guys like to call accelerated computing. And I want to tie that into storage performance. I got a question for both of you. I'll start with Matheen. When you're feeding GPUs with the right data, you've got to have it almost real time, near real time, even real time. How do your two companies, Dell and NVIDIA, how do you approach that challenge of being able to keep that data streaming, feeding the GPUs so that they stay highly utilized so you're not wasting that critical resource? Matheen, I wonder if you could start.
Matheen Raza
>> Yeah, for sure. One of the things is that we are not just accelerating the AI workloads, but we're accelerating a variety of different workloads. And a set of these include data prep. So, things like accelerating Spark with RAPIDS and helping those workloads run faster or accelerating vector indexing with cuVS and other CUDA, what we call the CUDA-X libraries that accelerate the workflow either in the data prep or post preparation of data. Basically, accelerating a variety of different workloads. We see that the enterprise data management or the storage systems need to be able to deliver these data pipelines to these workloads, to these accelerated computing workloads, whether it's a high-performance computing workload, whether it is a training workload or an inference workload, making sure that these GPUs that you have have the right amount of data, can operate on that real-time data. The analogy that I use is that if you're using a sports car, you don't want to drive it on inside streets and drive it at low speed. You want to make sure that you're maximizing the utilization of your sports car and be able to drive it and have the high-speed roads, in this case, the analogy would be the networking and high-performance storage, to be able to power your sports car or power your AI use cases with the right amount of data.
Dave Vellante
>> Okay, thank you. Darren, I wonder if you could give us your perspective from Dell's point of view?
Darren Miller
>> Yeah, sure. Matheen actually hit it right on the head. From the software stack, CUDA-X, RAPIDS, Spark that's pulling in data and it's accessing data at a rapid rate regardless of the workflow that's being run there. These libraries and these technologies are demanding data at a high speed. So, from Dell's perspective, especially on the storage side, we need to provide that data at a rapid rate and at a high-performance rate. And engineering advances in the past two to three years at Dell have provided more than double performance. And a lot of our products, including file and object storage, we've increased the capability to have higher capacity systems with introduction of 122 terabyte size disks, gains in improvements like this, not only just give us things to brag about for the most part, but also they provide the infrastructure that's needed for these higher performance workloads and the applications in the software stacks that are demanding that data at a rapid rate.
Dave Vellante
>> Okay. Let's talk about RAG workloads and the intelligence, the metadata intelligence around that. I'll start with Matheen. Retrieval Augmented Generation, it's become mainstream. People realize, wow, I got this corpus of data, I can vectorize it, I can do the embedding, and I can actually have an intelligent assistant and chatbot and I could serve customers better. I can serve my internal needs better, so many use cases. So, it's become a critical enterprise workload. How is it evolving and why, Matheen, is it so important today?
Matheen Raza
>> Yes, absolutely. It goes back to generative AI. Ever since it's come into the market, it's been the most transformative technology of our generation and pretty much every function, what we're seeing is it's going to be infused with AI to enhance what we are doing on a daily basis. But however good these models are, they need the enterprise context, they need the data, and this is where data becomes a critical piece. Otherwise, these models are not going to be efficient and they're not really going to deliver the value that they're intended to deliver. And RAG is the great way to augment that knowledge base. But for these agents or for these use cases, you want to make sure that you have the most current, the freshest data available for the models to make their predictions and deliver those responses. And from there on, drive outcomes out of that as well. What we are seeing happen is as enterprises start using or building with this, we see each team building their own RAG pipeline. They start copying data over and do so multiple times and essentially creating sprawl and bloat of data within the organization. It's not just inefficient. It also opens security and accuracy issues, which can really lead to some data privacy and compliance issues in most organizations. So, this is where we're seeing a new class of storage infrastructure emerge to support the needs of these AI workloads. We announced this as part of our initiative called NVIDIA AI Data Platform, which is a customizable reference design where we work with our partners such as Dell to build solutions that deliver, we're starting with RAG, but deliver these AI pipelines for these enterprise AI workloads.
Dave Vellante
>> And Darren, we know from our own experience using theCUBE AI and our own RAG-based interfaces and chatbots, you can't just throw it out there and expect it all to work. You've got to classify it, you've got to have strong indexing, you've got to have your metadata act together, you've got to have performance tuning. How are you guys addressing that and adding value to the portions of the solution that Matheen just talked about?
Darren Miller
>> We've talked a lot about storage efficiencies and performance advances as well as increased capacity capabilities, but one thing we haven't spoke of is metadata. If you think of RAG workflows and being able to retrieve that data on an extremely efficient rate to reduce lag time and responses and things like that, metadata is key. We recently announced a technology within the OneFS file system called MetadataIQ. And what MetadataIQ does is it essentially enhances classification of data, indexes your metadata in a way where it's easily read, it's easily accessible through these mechanisms like the RAG workflows and LangChain and things like that, which again, is another level of efficiency and brings that efficiency to the specific workflow instead of the data in general. Another thing that we recently announced was the PowerScale RAG connector. Essentially, what the RAG connector does is it further enhances that capability of accessing the data because the connector knows exactly where the data is placed within OneFS through our metadata mechanisms and MetadataIQ, and then allows lookup and retrieval rates to be even more efficient based off of the knowledge that that RAG connector has within the OneFS file system.
Dave Vellante
>> Guys, it's been a great conversation. Oh, go ahead. Please carry on, Darren.
Darren Miller
>> No, the only thing I was going to finish with was that the other thing that helps these workflows is integration with NVIDIA's NIM services and being able to tie that into the workflow almost organically, if you will, through different connectors and different technologies that enable those workflows.
Dave Vellante
>> Thank you for adding that. The NIM microservice is a key. Guys, I really appreciate your time. I wonder if you could put a bow on this conversation, just give us final thoughts. Maybe Darren, you could start and then Matheen, you can bring us home.
Darren Miller
>> Yeah, sure. I think the only thing I'll finish with is, first off, thank you Dave for hosting. It's been a pleasure as usual. We are hosting a Dell AI Data Platform event where we'll be showcasing new innovations within the Dell AI Data Platform, customer case studies, as well as specific workflows that will help customers to build better AI within their organizations. And we'll be showcasing some joint solutions with NVIDIA.
Dave Vellante
>> Matheen, your final thoughts?
Matheen Raza
>> This has been great conversation. Thank you for having me. And if you're looking to simplify scale and accelerate your AI within your organization, the Dell AI Data Platform event is the event to be at. We are really excited to continue our work with Dell and continue to push boundaries to deliver innovative solutions to our customers. Thank you.
Dave Vellante
>> Guys. Thank you. This is a complicated situation for a lot of customers, particularly in enterprises that have really frankly been relying on the cloud for many years for their infrastructure. They need solutions. The big hyperscalers, they've got the skills they can throw engineering time and money at the problem, customers need solutions and partnerships like this are critical. So, I really appreciate you guys getting together and sharing with us what you guys are doing and look forward to having you back. There's more coming later this fall on October 21st, the Dell AI Data Platform event, which is hosted by theCUBE, so look for that on thecube.net and on Dell's website, dell.com. Thank you guys. Really appreciate your time.
Matheen Raza
>> Thank you.
Darren Miller
>> Thank you.
Dave Vellante
>> All right. Thank you for watching. This is Dave Vellante for theCUBE, and we'll see you next time.
Dave Vellante