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Most AI/ML environments are nascent with fluid supporting technology and personn…
The typical AI data pipeline has a diverse storage infrastructure ecosystem.
Sensitive data and operationalizing AI/ML continue to be challenges across the…
Many see synergy between AI/ML and data lake technology.
Next-generation infrastructure solutions are increasingly deployed and considere…
Demographics
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ESG Master Survey Results: Supporting AI/ML Initiatives with a Modern Infrastructure Stack
ESG Master Survey Results
May 10, 2021
This Master Survey Results presentation focuses on organizations in the process of transforming their businesses with artificial intelligence to understand the evolving data storage requirements of the next-generation applications and workloads supporting AI initiatives.
ESG conducted a comprehensive online survey of IT operations professionals from private- and public-sector organizations in North America (United States and Canada) between September 17, 2020 and September 26, 2020. To qualify for this survey, respondents were required to be IT professionals familiar and involved with evaluating, purchasing, and managing storage associated with AI initiatives for their organizations.
Page Count: 47
Table of Contents
About This Document
Research Methodology
Most AI/ML environments are nascent with fluid supporting technology and personnel situations.
The typical AI data pipeline has a diverse storage infrastructure ecosystem.
Sensitive data and operationalizing AI/ML continue to be challenges across the data lifecycle.
Many see synergy between AI/ML and data lake technology.
Next-generation infrastructure solutions are increasingly deployed and considered to support AI/ML.