Why Data Quality is Crucial in the Age of AI with Adam Dille and Zeba Hasan
Modern CTO
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The Imperative of Data Quality in AI
This chapter discusses the growing importance of data quality as a strategic asset for successful AI implementations. It emphasizes the need for a reliable data foundation to avoid pitfalls like misleading AI outputs and highlights the risks of over-collecting data without clarity on critical metrics. Through practical examples, the chapter advocates for the integration of domain expertise in AI projects to enhance outcomes and customer experiences.
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