NetApp Case Study: Real-Time Predictive Maintenance & Advanced Analytics

NetApp Case Study

NetApp deployed Iguazio at the core of Active IQ, analyzing 10 trillion data points in real time from storage sensors worldwide to generate actionable intelligence and real-time predictive maintenance for their customers globally.

Read this case study to discover how NetApp unified their data engineering and data science infrastructure with Iguazio, driving the following gains: 


  • 6-12x improvement in time to develop and deploy new AI services
  • 50% reduction in operating costs
  • 16x storage capacity reduction
  • 3-6x fewer compute nodes
  • End-to-end platform for analytics and AI

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About Iguazio

Iguazio’s MLOps platform enables enterprises to build and deploy automated machine learning pipeline, drastically shortening the time required to create real business value with AI. Using Iguazio, organizations can accelerate deployment of AI to production and enable the continuous rollout and management of new AI services, even at scale and in real time. Iguazio can be deployed anywhere (multi-cloud, on-prem or hybrid), to bring to life your most ambitious AI-driven strategies. Enterprises spanning a wide range of verticals use Iguazio to solve the complexities of MLOps and create business impact through a multitude of use cases such as fraud prediction, real-time recommendation engines and predictive maintenance. Iguazio raised $72M and is partnered with dozens of technology companies including NetApp, NVIDIA, Dell, Intel, Microsoft, AWS and Google. Iguazio brings data science to life.

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