The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t
CIO Business Intelligence
JANUARY 20, 2023
2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security. It’s About the Data For companies that have succeeded in an AI and analytics deployment, data availability is a key performance indicator, according to a Harvard Business Review report. [3]
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