THE CRITICAL ROLE OF DATA ENGINEERING IN GENERATIVE AI
Keywords:
Generative AI, Data Engineering, AI Ethics, Machine Learning Infrastructure, AI ExplainabilityAbstract
This article explores the intricate relationship between data engineering and generative AI (Gen AI), highlighting the critical role that data engineering plays in the development, deployment, and optimization of Gen AI systems. It delves into the nature of generative AI and its revolutionary capabilities across various domains, from text and image generation to music composition and code creation. The symbiotic relationship between data engineering and Gen AI is examined in detail, covering key aspects such as data collection and curation, preprocessing and transformation, scalable infrastructure development, data versioning and governance, and continuous pipeline optimization. The article also addresses the emerging challenges and future directions in this field, including ethical data handling, real-time processing, multimodal data integration, and the need for explainable AI systems. By elucidating this critical interplay, the article underscores the importance of robust data engineering practices in realizing the full potential of generative AI technologies.
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