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Your 5-Step Journey from Analytics to AI

CIO Business Intelligence

Think it through, end to end, from implementation feasibility to identifying the key performance indicators (KPIs) you’ll use to measure return on investment (ROI) and project success. Ready to evolve your analytics strategy or improve your data quality? Focus on a specific business problem to be solved.

Analytics 115
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CIO Bhavani Amirthalingam on driving change in the AI era

CIO Business Intelligence

What key performance indicators are we going to look to say that we are at X, we need to get to Y, and we were able to get there. It has been around since the 1950s with machine learning. Talk to us about how leaders should be thinking about the role of data quality in terms of their AI deployments.

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The Reason Many AI and Analytics Projects Fail—and How to Make Sure Yours Doesn’t

CIO Business Intelligence

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]

Analytics 137