AI data centers are built to support demanding workloads, but powerful GPUs and accelerators can only deliver value when they can access the right data. They need data that is available, prepared, indexed, and governed. When information is fragmented across silos, AI deployments may struggle to meet their goals.
Fast access matters, but speed alone is not enough. Data also needs context and a path to the workload.
TL;DR
- AI factories can accelerate workloads only when models and applications can access well-labeled, indexed, searchable, and governed data
- Enterprise data may span on-premises systems, clouds, and SaaS environments. Dell AI Data Platform supports query-in-place where practical and efficient data movement where necessary, helping teams reduce unnecessary copies and keep data available to AI workloads
- Specialized data engines help teams query, process, search, index, and enrich structured and unstructured data for retrieval-augmented generation (RAG), analytics, and other AI workloads
- Security and cyber-resilience capabilities help protect data throughout the AI workflow
Faster storage isn’t an effective solution to data fragmentation. Although it can reduce I/O bottlenecks, it doesn’t solve the problems of data preparation, discovery, and governance.
With effectively labeled and indexed data on AI-optimized storage, Dell AI Data Platform helps deliver relevant context to AI models and applications exactly when they need it—all the while ensuring strong access control and encryption, with real-time threat detection ensuring security for sensitive data.
Do AI factories require a data rethink?
RAG and agentic AI can be constrained when data is difficult to reach, poorly labeled, or siloed behind multiple access layers. Dell AI Data Platform provides an open, modular foundation that helps prepare enterprise data for retrieval and serve it to AI workloads across on-premises, cloud, and edge environments.
Dell AI Data Platform brings storage engines, data engines, and orchestration together to turn enterprise data into AI outcomes
Working with data from a range of sources across various deployments, be they on-premises, in the cloud, or on the edge, Dell AI Data Platform leverages its data engines to ingest the raw data, process, and enrich it. Where appropriate, federated access helps teams query data in place and reduce unnecessary movement. Orchestration connects these steps across training, fine-tuning, retrieval, inference, and agentic workflows.
How does the Dell AI Data Platform make data AI-ready?
Dell AI Data Platform is built around four key data engines, each playing a key part in taking raw, structured, and unstructured data and optimizing it for AI use.
- Dell Data Analytics Engine, powered by Starburst, efficiently queries across large and distributed data sets using SQL. It helps teams analyze data where it lives and reduce unnecessary data movement.
- Dell Data Processing Engine can ingest data, enrich, filter, and transform it, ready for use by other data engines.
- Dell Data Search Engine, powered by Elasticsearch, supports full-text, vector, and hybrid search across structured and unstructured data. As source data changes, orchestrated pipelines can update indexes so applications can retrieve current context without relying on stale copies.
- Dell Data Orchestration Engine coordinates multimodal workflows across audio, text, documents, 3D data, and video. It helps automate discovery, enrichment, labeling, preparation, and refresh while preserving human oversight where needed.
Why does orchestration matter more as AI factories scale?
Fast storage remains foundational, but bandwidth alone does not solve siloed, poorly labeled, or fragmented data. As AI factories scale, the pipeline must connect storage, data preparation, search, governance, and the workload.
For training, it helps prepare organized datasets. For RAG, it helps keep enterprise knowledge searchable and current. For agentic AI, it helps connect governed data sources and workflows so applications can reason over relevant context. NVIDIA-accelerated data processing can help reduce bottlenecks as workloads scale.
If you think Dell AI Data Platform could benefit your business, find out more on the Dell website: US readers click here and CA readers here.