If your data is a mess, then (to prepare for machine learning and other analysis & inference methods) you need to spend a lot of time doing a lot of data profiling, data typing, data transformations (e.g., scaling, zero-centering, normalizations, adjusting for different units,
Preparing Messy Data for Machine Learning Requires Profiling and Normalization
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