Explore the critical importance of understanding and preparing data before model training in this 51-minute conference talk from Devoxx. Delve into common problems encountered during data analysis and preparation, including dirty data, disparate datasets requiring normalization, and information overload. Learn various techniques to address these issues, such as detecting misleading data and outliers, handling missing or ambiguous values, and applying dimensionality reduction. Discover how to use statistical and physics functions, feature selection, and resampling methods to enhance data quality. Gain insights into utilizing different types of plots at various stages of the data preparation process. Walk away with valuable resources to further explore data analysis and preparation techniques at your own pace, equipping yourself with essential skills for transitioning from developer to data scientist.