Gartner Research

Three Ways That AI Will Impact Your Data Management and Storage Strategy

Published: 27 August 2018

ID: G00351887

Analyst(s): Chirag Dekate , Julia Palmer , Arun Chandrasekaran

Summary

I&O leaders selecting infrastructure for AI workloads involving machine learning and deep learning must comprehend the unique requirements of these emerging workloads. We analyze the impact of AI workloads on data infrastructure and outline best practices for storage selection and implementation.

Table Of Contents
  • Impacts

Analysis

Impacts and Recommendations

  • Different Stages of AI Workloads Have Distinct I/O Characteristics, Requiring I&O Leaders to Deploy Complementary Storage Architectures
  • Unique Requirements of AI and ML Workloads Will Cause I&O Leaders to Re-evaluate Their Approach to Storage Selection and Embrace New Technology and Deployment Methods
  • The Vendor Ecosystem Supporting AI Workloads Is Nascent, but Fast Evolving, Exacerbating the Vendor Selection Process for I&O Leaders

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