AI Data Pipelines: Infrastructure Considerations

IDC’s guidance on how to approach AI deployments

Infrastructure Considerations for AI Data Pipelines reportArtificial intelligence (AI) is transforming how business processes are carried out in the digital era. But while AI's power and promise are exciting, it is not easy to deploy AI models and workloads. Most organizations are struggling through proofs of concept, and only a few have made it to full production. Building, testing, optimizing, training, inferencing, and maintaining the accuracy of models are integral to AI workflow.

Because AI effectiveness depends heavily on high-quality, diverse, dynamic, and distributed data sets, advanced data management is one of the top challenges for successful AI deployments.

Get IDC’s expert guidance on how to:

  • Build an end-to-end data pipeline
  • Accelerate AI-driven business outcomes
  • Overcome deployment obstacles

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NetApp and Nvidia’s partnership

Check out the "Accelerate Your Journey to AI with NetApp and NVIDIA" video and learn how to simplify, accelerate and integrate your data pipeline for deep learning with NetApp ONTAP AI, powered by NVIDIA DGX supercomputers and NetApp cloud-connected, all-flash storage.

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