Why Data Quality is Crucial in the Age of AI with Adam Dille and Zeba Hasan
Modern CTO
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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