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The tutorial focuses on exploring chocolate datasets using data visualization techniques to form initial hypotheses. The presenter emphasizes the difference between having data and extracting knowledge from it. The process involves several iterative steps: cleaning the data to enhance its utility, transforming it for combining datasets, and statistically measuring the results. Additionally, if the dataset is too large, data reduction may be necessary. This cycle of cleaning, transforming, and reducing will continue until the dataset is refined to its most useful form.