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Delve into the critical role of data quality in artificial intelligence (AI) systems, understanding its implications from fundamental scenarios to complex applications, such as medical diagnoses. The chapter elaborates on the significance of data preparation, encompassing both cleaning and normalization processes, to ensure the impeccable performance of AI models. Notably, the nuances of data augmentation are explored, highlighting its transformative potential in enhancing model performance, especially in the context of imbalanced datasets. By engaging with this content, professionals will gain pivotal insights into optimizing data for AI, with practical techniques and benefits that can be instrumental for any AI project.