How the right automated storage management boosts AI and analytics pipeline performance and reliability

TL;DR

• Intuitive automation tools help streamline data flows for AI training and inference
• Breaking down silos to create consistent data pipelines is critical for AI innovation
• Dell PowerScale and the OneFS operating system support AI workloads with scale-out storage, intelligent data placement, analytics, and metadata tools

AI is data-hungry, and both training and inference processes require a consistent pipeline to ensure streamlined flows and, ultimately, success.

Yet storage infrastructure limitations have often been a key hurdle for organizations, creating bottlenecks, hampering performance, and severely impacting innovation projects.

The need for high-performance storage infrastructure has prompted a wave of investment across a range of industries over the last three years to meet these changing needs.

Analysis from IDC in October 2025, for example, noted that spending on AI infrastructure, particularly storage, has been “driven by the need to manage large datasets required for training AI models”.

Investment has also surged because storage is needed for data used in inference processes further down the line as enterprise AI adoption projects mature and expand.

The underlying infrastructure needed to fuel enterprise AI adoption is only one side of the equation, however. The platforms and solutions leveraged by infrastructure operations and IT teams need to deliver tangible business value.

That means considerations such as flexibility, scalability, cost efficiency, performance, and crucially, ease of use, are all leading factors in buying decisions.

“Large-scale GenAI deployments will require distinct storage performance and data management capabilities for the data ingestion, training, inference, and archiving stages of the GenAI workflow,” the company noted in a research paper.

Enterprises choosing storage solutions need to take these factors into account. This is where platforms such as Dell PowerScale offer significant value for IT leaders.

Dell PowerScale is a scale-out network-attached storage (NAS) platform designed specifically for storing and managing vast volumes of unstructured data, the lifeblood of AI.

So what makes PowerScale effective for AI and analytics performance? The sheer scale of in-built features, tools, and automation capabilities makes it a go-to option for organizations.

Indeed, the platform is trusted by more than 25,000 customers globally – with 1,500+ running GPU workloads, according to official Dell figures.

Dell PowerScale: Intelligent scaling

Underpinning PowerScale is the OneFS operating system, the software-based heart of the storage platform.

The OS plays a key role in enabling users to both scale storage infrastructure while also helping to streamline and optimize management capabilities for teams working on the frontline.

“OneFS is designed to scale not just in terms of machines, but also in human terms - allowing large-scale systems to be managed with a fraction of the personnel required for traditional storage systems,” according to Dell.

As noted, scalability is a key focus for the PowerScale platform, allowing enterprises to expand infrastructure based on their individual needs and evolving requirements.

PowerScale allows for intelligent scaling, rather than a potentially costly one-size-fits-all approach. The system distributes datasets based on the availability of nodes within a cluster, helping to optimize performance and efficiency.

Intelligent data placement features are also a key differentiator for PowerScale, allowing users to automatically move data between a range of storage tiers, such as HDD, SSD, and NVMe.

This feature works by selecting the appropriate tier based on the content of an individual dataset. For example, NVMe storage may be selected for high-performance workloads, such as AI.

According to Dell, intelligent scaling and data placement capabilities, combined with the platform’s 2:1 Data Reduction Guarantee, have marked benefits both in terms of improving efficiency and reducing the total cost of ownership (TCO).

High-performance capabilities

PowerScale is a flexible platform designed for both AI training and inference purposes. From a performance perspective, PowerScale provides organizations with eight times greater cluster throughput compared to traditional flash-only competitors, with three times greater write throughput per rack unit.

This provides huge efficiency gains and the lower latency needed to ensure streamlined data flows to GPU clusters – a key consideration, according to 2026 research from Forrester.

“Unlike traditional analytics, enterprise-class AI inference depends on continuous, governed access to enterprise data. This demands more from infrastructure platforms, especially storage,” said Forrester principal analyst Brett Ellis in a May 2026 blog post.

Given research from McKinsey predicts inference workloads will account for over half of all AI workloads by 2030, PowerScale presents an opportunity for organizations to future-proof their infrastructure and compensate for evolving demands.

Consolidation

Many organizations contend with sprawling, disparate IT and infrastructure environments, which have a direct impact on efficiency, performance, and cost.

PowerScale, however, enables organizations to consolidate data within a single ecosystem, helping create a more manageable infrastructure environment that breaks down troublesome data silos.

These have proven to be a recurring pain point for organizations in recent years, with research from IDC ranking data silos among the “top barriers to scaling” AI.

Similar research from Accenture also identified silos as a key impediment to AI innovation, noting that IT leaders should focus heavily on breaking down barriers to build a stronger data foundation.

“Invest in breaking down data silos and building an end-to-end data foundation with quality data,” the consultancy said in a 2025 report.

Intuitive analytics capabilities

For infrastructure operations teams, PowerScale offers a range of intuitive automation features aimed at reducing manual toil and simplifying data management capabilities.

Built-in analytics tools, such as InsightIQ, enable real-time performance monitoring to help optimize applications and forecast future storage needs. These analytics capabilities are vital for organizations scaling out their architecture as they grow.

Elsewhere, the MetadataIQ feature enables customers to index data used in specific workflows. Per official Dell materials, this “metadata catalog” can be used for querying data points, visualization practices, and even data lifecycle management.

“As customers add analytics workflows, the ability to simply and efficiently query data, wherever it may reside, is vital for the time-to-results they require,” the company noted in a technical document.

If you think PowerScale is the right storage solution for your business, find out more on the Dell website: US readers click here.