Delivering data pipelines for enterprise AI

Resolve the bottlenecks to drive insights and action


Data-Pipeline-for-Enterprise-AI

Few areas of enterprise technology are advancing as fast as artificial intelligence right now. For many years, AI and machine learning have been the domain of the few, but in this era of increasingly low-cost compute and ever expanding pools of data, enterprises are... wait a minute, did somebody mention data?

Yes, data.

Even with the increasingly skilled-up ecosystem, delivering an ability to create more complex models and understanding how best to use the insights, the magnitude of potential data available to both learning and inference is causing problems of its own.

Throughput bottlenecks, architecture and integration issues, from resiliency, security and governance are just a few of the pesky challenges that get in the way of ensuring that AI’s data needs are met. They are not going away any time soon, what with the rise of the Internet of Things and resulting wave of new, massively distributed data sources.

So, what to do?

In this webinar, we sit down with ​Bharat Badrinath, NetApp VP of Flash Product Marketing and Santosh Rao, NetApp’s Senior Technical Director for AI & Data Engineering to understand what's driving the need for a comprehensive data foundation for AI. Drawing on examples from automotive, telco, healthcare, public and other sectors, we’ll cover:

  • trends driving the upswing in the use of AI in today’s enterprise businesses
  • what the data pipeline looks like for AI, across edge, core and cloud-based systems
  • how to build a comprehensive data foundation to meet the needs of AI today and tomorrow
  • where to start, from defining a need through to mapping options onto an AI-readydata architecture

So, if you are looking to start your enterprise AI journey off on the right foot, or your're already some way down the line but are tangling with data-related issues, tune in!

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